Many of us ignore CS fundamentals, but in many tech interviews they will ask CS fundamentals. For me, they asked only CS fundamentals in all 3 interviews at Oracle, So don't ignore CS fundamentals. I have made a list of important topics subject-wise and resources I have used to study at the end.

Interview prep resource: Leetcode & PracHub for Company specific questions

Object-Oriented Programming (OOPs)

Core Concepts

• Encapsulation
• Inheritance (types and use cases)
• Polymorphism (compile-time vs runtime)
• Abstraction
• Abstract Class vs Interface
• Method Overloading vs Overriding
• Access Modifiers
• Static vs Dynamic Binding
• Deep Copy vs Shallow Copy

Advanced Topics

• SOLID Principles
• Diamond Problem (Multiple Inheritance)
• Association vs Aggregation vs Composition
• Virtual Functions and Vtable
• Design Patterns (Singleton, Factory, Observer, Strategy, Decorator, Adapter)

Operating Systems (OS)

Process Management

• Process vs Thread
• Process States and PCB
• Context Switching
• CPU Scheduling Algorithms (FCFS, SJF, Round Robin, Priority)
• Multithreading vs Multiprocessing
• User Mode vs Kernel Mode

Synchronization

• Critical Section Problem
• Race Condition
• Mutex vs Semaphore (Binary vs Counting)
• Monitors and Locks
• Producer-Consumer Problem
• Readers-Writers Problem
• Dining Philosophers Problem

Deadlocks

• Deadlock Conditions (4 necessary conditions)
• Deadlock Prevention vs Avoidance vs Detection
• Banker's Algorithm

Memory Management

• Paging vs Segmentation
• Page Replacement Algorithms (FIFO, LRU, Optimal)
• Thrashing
• Virtual Memory
• TLB (Translation Lookaside Buffer)
• Internal vs External Fragmentation

File Systems & Disk

• File Allocation Methods (Contiguous, Linked, Indexed)
• Disk Scheduling (FCFS, SSTF, SCAN, C-SCAN)

Database Management Systems (DBMS) + SQL

Database Fundamentals

• ACID Properties (with examples)
• CAP Theorem
• Normalization (1NF, 2NF, 3NF, BCNF)
• Denormalization
• Primary Key vs Foreign Key vs Candidate Key
• ER Diagrams

Indexing

• Types of Indexes (Primary, Secondary, Clustering)
• B-Tree vs B+ Tree
• Hash Index
• Composite Index
• Advantages and Disadvantages of Indexing

Transactions & Concurrency

• Transaction Lifecycle
• Isolation Levels (Read Uncommitted, Read Committed, Repeatable Read, Serializable)
• Dirty Read, Non-repeatable Read, Phantom Read
• Lost Update Problem
• Two-Phase Locking (2PL)
• Optimistic vs Pessimistic Locking
• Deadlock in Database

SQL Queries (Must Practice)

• JOINs (INNER, LEFT, RIGHT, FULL OUTER, CROSS, SELF)
• GROUP BY and HAVING
• Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)
• Subqueries (Correlated vs Non-correlated)
• Window Functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG)
• Common Table Expressions (CTE)
• UNION vs UNION ALL
• Nth Highest Salary Query
• Delete Duplicates Query

NoSQL

• SQL vs NoSQL
• Types of NoSQL Databases (Document, Key-Value, Column, Graph)

Computer Networks (CN)

Network Models

• OSI Model (7 Layers)
• TCP/IP Model (4 Layers)
• Difference between OSI and TCP/IP

Application Layer

• HTTP vs HTTPS
• HTTP Methods (GET, POST, PUT, DELETE, PATCH)
• HTTP Status Codes (2xx, 3xx, 4xx, 5xx)
• DNS and its working
• FTP, SMTP, POP3, IMAP
• Cookies vs Sessions
• REST API principles

Transport Layer

• TCP vs UDP (detailed comparison)
• TCP Three-Way Handshake
• TCP Four-Way Termination
• Flow Control (Sliding Window)
• Congestion Control
• Port Numbers (well-known ports)
• Socket Programming Basics

Network Layer

• IPv4 vs IPv6
• Public vs Private IP
• Subnetting and CIDR
• NAT (Network Address Translation)
• ICMP Protocol
• Routing Algorithms (Distance Vector, Link State)
• Routing Protocols (RIP, OSPF, BGP)

Data Link Layer

• MAC Address
• ARP (Address Resolution Protocol)
• Switch vs Hub vs Router
• Ethernet
• Error Detection (Parity, CRC, Checksum)

Physical Layer

• Transmission Media (Guided vs Unguided)
• Bandwidth and Throughput
• Different Topologies

Important Concepts

• Client-Server vs Peer-to-Peer Architecture
• DHCP
• Firewall
• VPN
• Load Balancing
• CDN (Content Delivery Network)
• Latency vs Throughput
• How does a URL work? (End-to-end flow)
• Some Basic Commands (ex: ipconfig)

Resources I Used

For OOPs

• Kunal Kushwaha (youtube channel)

For Operating Systems

• CodeHelp - by Babbar (youtube )

For DBMS + SQL

• LeetCode Database problems (Practice SQL)
• CodeHelp - by Babbar (youtube)
• Apna College (youtube)

For Computer Networks

• Gate Smashers (youtube)

Questions Asked in My Interviews

Here are some actual questions I was asked across my interviews:

1. Is Java fully object-oriented?
2. How does C++ overcome the diamond problem?
3. Difference between TCP and UDP, and which one is used when?
4. Explain ACID properties with examples
5. What is deadlock and how can we prevent deadlocks?
6. What is the use of indexing in databases?
7. Explain the functionalities of each layer in the OSI model
8. Write a query to find Kth smallest salary
9. IPv4 vs IPv6
10. Abstraction vs Encapsulation
11. Explain different joins in dbms
12. what is sharding ?
13. what is virtual function in cpp ?
14. show me your ip address and mac address using commands
15. what is context switching ?

Tips :

1. Make sure you can explain concepts with real-world examples
2. Revise SQL 50 before interviews
3. It's better to say "I'm not sure about this, but here's what I think..." than to give wrong information
4. If your project contains any database related stuff , better learn it's ER diagram, differences between SQl and NO-SQl and why you selected that particular database you used
5. Before preparing for any interview , First check few interview experiences, Ask your seniors or friends who already attended that specific company interviews before and prepare accordingly

Did I miss any important topic? Drop it in the comments below!

Got asked something unique in your interview? Share the question/topic so others can prepare better!

Let's make this list more comprehensive together. Your contribution can help someone crack their dream job! 🙌

Good luck with your interviews! 🚀

Many of us ignore CS fundamentals, but in many tech interviews they will ask CS fundamentals. For me, they asked only CS fundamentals in all 3 interviews at Oracle, So don't ignore CS fundamentals. I have made a list of important topics subject-wise and resources I have used to study at the end.

Interview prep resource: Leetcode & PracHub for Company specific questions

Object-Oriented Programming (OOPs)

Core Concepts

• Encapsulation
• Inheritance (types and use cases)
• Polymorphism (compile-time vs runtime)
• Abstraction
• Abstract Class vs Interface
• Method Overloading vs Overriding
• Access Modifiers
• Static vs Dynamic Binding
• Deep Copy vs Shallow Copy

Advanced Topics

• SOLID Principles
• Diamond Problem (Multiple Inheritance)
• Association vs Aggregation vs Composition
• Virtual Functions and Vtable
• Design Patterns (Singleton, Factory, Observer, Strategy, Decorator, Adapter)

Operating Systems (OS)

Process Management

• Process vs Thread
• Process States and PCB
• Context Switching
• CPU Scheduling Algorithms (FCFS, SJF, Round Robin, Priority)
• Multithreading vs Multiprocessing
• User Mode vs Kernel Mode

Synchronization

• Critical Section Problem
• Race Condition
• Mutex vs Semaphore (Binary vs Counting)
• Monitors and Locks
• Producer-Consumer Problem
• Readers-Writers Problem
• Dining Philosophers Problem

Deadlocks

• Deadlock Conditions (4 necessary conditions)
• Deadlock Prevention vs Avoidance vs Detection
• Banker's Algorithm

Memory Management

• Paging vs Segmentation
• Page Replacement Algorithms (FIFO, LRU, Optimal)
• Thrashing
• Virtual Memory
• TLB (Translation Lookaside Buffer)
• Internal vs External Fragmentation

File Systems & Disk

• File Allocation Methods (Contiguous, Linked, Indexed)
• Disk Scheduling (FCFS, SSTF, SCAN, C-SCAN)

Database Management Systems (DBMS) + SQL

Database Fundamentals

• ACID Properties (with examples)
• CAP Theorem
• Normalization (1NF, 2NF, 3NF, BCNF)
• Denormalization
• Primary Key vs Foreign Key vs Candidate Key
• ER Diagrams

Indexing

• Types of Indexes (Primary, Secondary, Clustering)
• B-Tree vs B+ Tree
• Hash Index
• Composite Index
• Advantages and Disadvantages of Indexing

Transactions & Concurrency

• Transaction Lifecycle
• Isolation Levels (Read Uncommitted, Read Committed, Repeatable Read, Serializable)
• Dirty Read, Non-repeatable Read, Phantom Read
• Lost Update Problem
• Two-Phase Locking (2PL)
• Optimistic vs Pessimistic Locking
• Deadlock in Database

SQL Queries (Must Practice)

• JOINs (INNER, LEFT, RIGHT, FULL OUTER, CROSS, SELF)
• GROUP BY and HAVING
• Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)
• Subqueries (Correlated vs Non-correlated)
• Window Functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG)
• Common Table Expressions (CTE)
• UNION vs UNION ALL
• Nth Highest Salary Query
• Delete Duplicates Query

NoSQL

• SQL vs NoSQL
• Types of NoSQL Databases (Document, Key-Value, Column, Graph)

Computer Networks (CN)

Network Models

• OSI Model (7 Layers)
• TCP/IP Model (4 Layers)
• Difference between OSI and TCP/IP

Application Layer

• HTTP vs HTTPS
• HTTP Methods (GET, POST, PUT, DELETE, PATCH)
• HTTP Status Codes (2xx, 3xx, 4xx, 5xx)
• DNS and its working
• FTP, SMTP, POP3, IMAP
• Cookies vs Sessions
• REST API principles

Transport Layer

• TCP vs UDP (detailed comparison)
• TCP Three-Way Handshake
• TCP Four-Way Termination
• Flow Control (Sliding Window)
• Congestion Control
• Port Numbers (well-known ports)
• Socket Programming Basics

Network Layer

• IPv4 vs IPv6
• Public vs Private IP
• Subnetting and CIDR
• NAT (Network Address Translation)
• ICMP Protocol
• Routing Algorithms (Distance Vector, Link State)
• Routing Protocols (RIP, OSPF, BGP)

Data Link Layer

• MAC Address
• ARP (Address Resolution Protocol)
• Switch vs Hub vs Router
• Ethernet
• Error Detection (Parity, CRC, Checksum)

Physical Layer

• Transmission Media (Guided vs Unguided)
• Bandwidth and Throughput
• Different Topologies

Important Concepts

• Client-Server vs Peer-to-Peer Architecture
• DHCP
• Firewall
• VPN
• Load Balancing
• CDN (Content Delivery Network)
• Latency vs Throughput
• How does a URL work? (End-to-end flow)
• Some Basic Commands (ex: ipconfig)

Resources I Used

For OOPs

• Kunal Kushwaha (youtube channel)

For Operating Systems

• CodeHelp - by Babbar (youtube )

For DBMS + SQL

• LeetCode Database problems (Practice SQL)
• CodeHelp - by Babbar (youtube)
• Apna College (youtube)

For Computer Networks

• Gate Smashers (youtube)

Questions Asked in My Interviews

Here are some actual questions I was asked across my interviews:

1. Is Java fully object-oriented?
2. How does C++ overcome the diamond problem?
3. Difference between TCP and UDP, and which one is used when?
4. Explain ACID properties with examples
5. What is deadlock and how can we prevent deadlocks?
6. What is the use of indexing in databases?
7. Explain the functionalities of each layer in the OSI model
8. Write a query to find Kth smallest salary
9. IPv4 vs IPv6
10. Abstraction vs Encapsulation
11. Explain different joins in dbms
12. what is sharding ?
13. what is virtual function in cpp ?
14. show me your ip address and mac address using commands
15. what is context switching ?

Tips :

1. Make sure you can explain concepts with real-world examples
2. Revise SQL 50 before interviews
3. It's better to say "I'm not sure about this, but here's what I think..." than to give wrong information
4. If your project contains any database related stuff , better learn it's ER diagram, differences between SQl and NO-SQl and why you selected that particular database you used
5. Before preparing for any interview , First check few interview experiences, Ask your seniors or friends who already attended that specific company interviews before and prepare accordingly

Did I miss any important topic? Drop it in the comments below!

Got asked something unique in your interview? Share the question/topic so others can prepare better!

Let's make this list more comprehensive together. Your contribution can help someone crack their dream job! 🙌

Good luck with your interviews! 🚀

Many of us ignore CS fundamentals, but in many tech interviews they will ask CS fundamentals. For me, they asked only CS fundamentals in all 3 interviews at Oracle, So don't ignore CS fundamentals. I have made a list of important topics subject-wise and resources I have used to study at the end.

Interview prep resource: Leetcode & PracHub for Company specific questions

Object-Oriented Programming (OOPs)

Core Concepts

• Encapsulation
• Inheritance (types and use cases)
• Polymorphism (compile-time vs runtime)
• Abstraction
• Abstract Class vs Interface
• Method Overloading vs Overriding
• Access Modifiers
• Static vs Dynamic Binding
• Deep Copy vs Shallow Copy

Advanced Topics

• SOLID Principles
• Diamond Problem (Multiple Inheritance)
• Association vs Aggregation vs Composition
• Virtual Functions and Vtable
• Design Patterns (Singleton, Factory, Observer, Strategy, Decorator, Adapter)

Operating Systems (OS)

Process Management

• Process vs Thread
• Process States and PCB
• Context Switching
• CPU Scheduling Algorithms (FCFS, SJF, Round Robin, Priority)
• Multithreading vs Multiprocessing
• User Mode vs Kernel Mode

Synchronization

• Critical Section Problem
• Race Condition
• Mutex vs Semaphore (Binary vs Counting)
• Monitors and Locks
• Producer-Consumer Problem
• Readers-Writers Problem
• Dining Philosophers Problem

Deadlocks

• Deadlock Conditions (4 necessary conditions)
• Deadlock Prevention vs Avoidance vs Detection
• Banker's Algorithm

Memory Management

• Paging vs Segmentation
• Page Replacement Algorithms (FIFO, LRU, Optimal)
• Thrashing
• Virtual Memory
• TLB (Translation Lookaside Buffer)
• Internal vs External Fragmentation

File Systems & Disk

• File Allocation Methods (Contiguous, Linked, Indexed)
• Disk Scheduling (FCFS, SSTF, SCAN, C-SCAN)

Database Management Systems (DBMS) + SQL

Database Fundamentals

• ACID Properties (with examples)
• CAP Theorem
• Normalization (1NF, 2NF, 3NF, BCNF)
• Denormalization
• Primary Key vs Foreign Key vs Candidate Key
• ER Diagrams

Indexing

• Types of Indexes (Primary, Secondary, Clustering)
• B-Tree vs B+ Tree
• Hash Index
• Composite Index
• Advantages and Disadvantages of Indexing

Transactions & Concurrency

• Transaction Lifecycle
• Isolation Levels (Read Uncommitted, Read Committed, Repeatable Read, Serializable)
• Dirty Read, Non-repeatable Read, Phantom Read
• Lost Update Problem
• Two-Phase Locking (2PL)
• Optimistic vs Pessimistic Locking
• Deadlock in Database

SQL Queries (Must Practice)

• JOINs (INNER, LEFT, RIGHT, FULL OUTER, CROSS, SELF)
• GROUP BY and HAVING
• Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)
• Subqueries (Correlated vs Non-correlated)
• Window Functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG)
• Common Table Expressions (CTE)
• UNION vs UNION ALL
• Nth Highest Salary Query
• Delete Duplicates Query

NoSQL

• SQL vs NoSQL
• Types of NoSQL Databases (Document, Key-Value, Column, Graph)

Computer Networks (CN)

Network Models

• OSI Model (7 Layers)
• TCP/IP Model (4 Layers)
• Difference between OSI and TCP/IP

Application Layer

• HTTP vs HTTPS
• HTTP Methods (GET, POST, PUT, DELETE, PATCH)
• HTTP Status Codes (2xx, 3xx, 4xx, 5xx)
• DNS and its working
• FTP, SMTP, POP3, IMAP
• Cookies vs Sessions
• REST API principles

Transport Layer

• TCP vs UDP (detailed comparison)
• TCP Three-Way Handshake
• TCP Four-Way Termination
• Flow Control (Sliding Window)
• Congestion Control
• Port Numbers (well-known ports)
• Socket Programming Basics

Network Layer

• IPv4 vs IPv6
• Public vs Private IP
• Subnetting and CIDR
• NAT (Network Address Translation)
• ICMP Protocol
• Routing Algorithms (Distance Vector, Link State)
• Routing Protocols (RIP, OSPF, BGP)

Data Link Layer

• MAC Address
• ARP (Address Resolution Protocol)
• Switch vs Hub vs Router
• Ethernet
• Error Detection (Parity, CRC, Checksum)

Physical Layer

• Transmission Media (Guided vs Unguided)
• Bandwidth and Throughput
• Different Topologies

Important Concepts

• Client-Server vs Peer-to-Peer Architecture
• DHCP
• Firewall
• VPN
• Load Balancing
• CDN (Content Delivery Network)
• Latency vs Throughput
• How does a URL work? (End-to-end flow)
• Some Basic Commands (ex: ipconfig)

Resources I Used

For OOPs

• Kunal Kushwaha (youtube channel)

For Operating Systems

• CodeHelp - by Babbar (youtube )

For DBMS + SQL

• LeetCode Database problems (Practice SQL)
• CodeHelp - by Babbar (youtube)
• Apna College (youtube)

For Computer Networks

• Gate Smashers (youtube)

Questions Asked in My Interviews

Here are some actual questions I was asked across my interviews:

1. Is Java fully object-oriented?
2. How does C++ overcome the diamond problem?
3. Difference between TCP and UDP, and which one is used when?
4. Explain ACID properties with examples
5. What is deadlock and how can we prevent deadlocks?
6. What is the use of indexing in databases?
7. Explain the functionalities of each layer in the OSI model
8. Write a query to find Kth smallest salary
9. IPv4 vs IPv6
10. Abstraction vs Encapsulation
11. Explain different joins in dbms
12. what is sharding ?
13. what is virtual function in cpp ?
14. show me your ip address and mac address using commands
15. what is context switching ?

Tips :

1. Make sure you can explain concepts with real-world examples
2. Revise SQL 50 before interviews
3. It's better to say "I'm not sure about this, but here's what I think..." than to give wrong information
4. If your project contains any database related stuff , better learn it's ER diagram, differences between SQl and NO-SQl and why you selected that particular database you used
5. Before preparing for any interview , First check few interview experiences, Ask your seniors or friends who already attended that specific company interviews before and prepare accordingly

Did I miss any important topic? Drop it in the comments below!

Got asked something unique in your interview? Share the question/topic so others can prepare better!

Let's make this list more comprehensive together. Your contribution can help someone crack their dream job! 🙌

Good luck with your interviews! 🚀

Applied for the SDE-1 role at Rippling on 6 April.

Timeline:

• 13 April: Got a mail from HR to schedule a 15-minute introductory call.
• 14 April: HR round happened. Mostly discussed my background, current work, past experience, and interview availability.
• 16 April: Received schedules for 2 technical rounds:
• Coding Round (1 hour) — 21 April
• LLD Round (1 hour) — 22 April

Coding Round:

• Asked a graph-based problem mainly around Topological Sort , saw this exact question on PracHub.

LLD Round:

• Started with a DFS-based approach for a graph problem.
• Follow-up questions gradually turned it into a shortest path problem.
• Discussed solutions using Dijkstra and then Bellman-Ford.
• Overall, both rounds went well from my side.

After multiple follow-ups, on 27 April I received a mail to share availability for the Hiring Manager round.

• Initially scheduled for 29 April.
• On 28 April, it got rescheduled to 30 April due to interviewer availability.

30 April HM Round:

• Unfortunately, I had internet issues during the introduction itself.
• Interviewer suggested rescheduling since he was fully booked for the day.
• It was then rescheduled again.

Further reschedules:

• Rescheduled to 6 May.
• On 6 May, got another mail saying interviewer was unavailable, so it moved to the next week (13 May).

Finally, on 13 May, I received this update:

“The roles have gone on hold for now. We will get back once we have a role in the near future.”

About me:

• Currently working as an SDE at a product-based company.
• Around 1 year of full-time experience.

Wanted to ask:

• Has anyone else received similar feedback from Rippling?
• Did they actually get back later?
• Should I continue following up with HR/recruiter after some time, or just move on?

Interview prep resource: LeetCode, Alex Xu & PracHub

#rippling #interview #interviewexpierence

Applied for the SDE-1 role at Rippling on 6 April.

Timeline:

• 13 April: Got a mail from HR to schedule a 15-minute introductory call.
• 14 April: HR round happened. Mostly discussed my background, current work, past experience, and interview availability.
• 16 April: Received schedules for 2 technical rounds:
• Coding Round (1 hour) — 21 April
• LLD Round (1 hour) — 22 April

Coding Round:

• Asked a graph-based problem mainly around Topological Sort , saw this exact question on PracHub.

LLD Round:

• Started with a DFS-based approach for a graph problem.
• Follow-up questions gradually turned it into a shortest path problem.
• Discussed solutions using Dijkstra and then Bellman-Ford.
• Overall, both rounds went well from my side.

After multiple follow-ups, on 27 April I received a mail to share availability for the Hiring Manager round.

• Initially scheduled for 29 April.
• On 28 April, it got rescheduled to 30 April due to interviewer availability.

30 April HM Round:

• Unfortunately, I had internet issues during the introduction itself.
• Interviewer suggested rescheduling since he was fully booked for the day.
• It was then rescheduled again.

Further reschedules:

• Rescheduled to 6 May.
• On 6 May, got another mail saying interviewer was unavailable, so it moved to the next week (13 May).

Finally, on 13 May, I received this update:

“The roles have gone on hold for now. We will get back once we have a role in the near future.”

About me:

• Currently working as an SDE at a product-based company.
• Around 1 year of full-time experience.

Wanted to ask:

• Has anyone else received similar feedback from Rippling?
• Did they actually get back later?
• Should I continue following up with HR/recruiter after some time, or just move on?

Interview prep resource: LeetCode, Alex Xu & PracHub

#rippling #interview #interviewexpierence

Applied for the SDE-1 role at Rippling on 6 April.

Timeline:

• 13 April: Got a mail from HR to schedule a 15-minute introductory call.
• 14 April: HR round happened. Mostly discussed my background, current work, past experience, and interview availability.
• 16 April: Received schedules for 2 technical rounds:
• Coding Round (1 hour) — 21 April
• LLD Round (1 hour) — 22 April

Coding Round:

• Asked a graph-based problem mainly around Topological Sort , saw this exact question on PracHub.

LLD Round:

• Started with a DFS-based approach for a graph problem.
• Follow-up questions gradually turned it into a shortest path problem.
• Discussed solutions using Dijkstra and then Bellman-Ford.
• Overall, both rounds went well from my side.

After multiple follow-ups, on 27 April I received a mail to share availability for the Hiring Manager round.

• Initially scheduled for 29 April.
• On 28 April, it got rescheduled to 30 April due to interviewer availability.

30 April HM Round:

• Unfortunately, I had internet issues during the introduction itself.
• Interviewer suggested rescheduling since he was fully booked for the day.
• It was then rescheduled again.

Further reschedules:

• Rescheduled to 6 May.
• On 6 May, got another mail saying interviewer was unavailable, so it moved to the next week (13 May).

Finally, on 13 May, I received this update:

“The roles have gone on hold for now. We will get back once we have a role in the near future.”

About me:

• Currently working as an SDE at a product-based company.
• Around 1 year of full-time experience.

Wanted to ask:

• Has anyone else received similar feedback from Rippling?
• Did they actually get back later?
• Should I continue following up with HR/recruiter after some time, or just move on?

Interview prep resource: LeetCode, Alex Xu & PracHub

#rippling #interview #interviewexpierence

Applied for the SDE-1 role at Rippling on 6 April.

Timeline:

• 13 April: Got a mail from HR to schedule a 15-minute introductory call.
• 14 April: HR round happened. Mostly discussed my background, current work, past experience, and interview availability.
• 16 April: Received schedules for 2 technical rounds:
• Coding Round (1 hour) — 21 April
• LLD Round (1 hour) — 22 April

Coding Round:

• Asked a graph-based problem mainly around Topological Sort , saw this exact question on PracHub.

LLD Round:

• Started with a DFS-based approach for a graph problem.
• Follow-up questions gradually turned it into a shortest path problem.
• Discussed solutions using Dijkstra and then Bellman-Ford.
• Overall, both rounds went well from my side.

After multiple follow-ups, on 27 April I received a mail to share availability for the Hiring Manager round.

• Initially scheduled for 29 April.
• On 28 April, it got rescheduled to 30 April due to interviewer availability.

30 April HM Round:

• Unfortunately, I had internet issues during the introduction itself.
• Interviewer suggested rescheduling since he was fully booked for the day.
• It was then rescheduled again.

Further reschedules:

• Rescheduled to 6 May.
• On 6 May, got another mail saying interviewer was unavailable, so it moved to the next week (13 May).

Finally, on 13 May, I received this update:

“The roles have gone on hold for now. We will get back once we have a role in the near future.”

About me:

• Currently working as an SDE at a product-based company.
• Around 1 year of full-time experience.

Wanted to ask:

• Has anyone else received similar feedback from Rippling?
• Did they actually get back later?
• Should I continue following up with HR/recruiter after some time, or just move on?

Interview prep resource: LeetCode, Alex Xu & PracHub

#rippling #interview #interviewexpierence

Slightly unusual entry point: I'd interviewed here a few months back and didn't get through, but the recruiter still had my profile and reached out again for a new opening. Because I'd already cleared the OA in the earlier process, I was moved straight to the interview rounds this time — no fresh assessment. Worth knowing that a past "reject" doesn't reset you to zero; you can re-enter the pipeline further along.

Round 1 — DSA

• Q1: Course Schedule II — classic topological sort. Recognized it on sight, went straight to Kahn's algorithm (BFS on in-degrees), returned a valid ordering and handled the cycle → empty-result case.
• Q2: Given an integer as a string, count the ways to split it into prime numbers, where (i) digits stay in the given order and (ii) the entire string is used.s = "11375" -> 3 [11, 37, 5], [11, 3, 7, 5], [113, 7, 5] This is partition DP — recurse over prefixes, check each piece for primality, memoize on start index. Walked through the recursion, the primality check, and the memoization to bring it down from exponential.

Round 2 — LLD

Design a Watch Party system: a host creates a virtual room, users join via a unique Room ID, and everyone watches a movie in sync. Must support real-time Play / Pause / Seek / Change-Playback-Speed, with all participants kept on the same playback state.

Core of it is real-time state synchronization — I modeled it as an Observer pattern over a shared playback state (host action → broadcast state delta → all clients reconcile), plus the Room/Participant/PlaybackState entities and how late-joiners get the current state on connect.

Round 3 — HM (in person)

Started with resume questions, then: whiteboard the high-level architecture of my current project and explain it. Be ready to do this cold — it's a common opener.

Then a separate HLD: design a system for renting out a ground/venue to organizations (schools, societies, event organizers), bookable through different rental packages. Discussion centered on core entities, DB schema, API design, and the relationships between components (venue ↔ package ↔ booking ↔ organization).

Verdict: Selected!!

Prep notes

• Course Schedule II I recognized as topological sort instantly and had Kahn's out without thinking; the prime-split problem I mapped to partition DP within the first read. Neither needed deriving from scratch, because I'd drilled topo-sort and partition-DP patterns on PracHub until recognition was reflexive. On a timed round that head start is everything — it's the difference between spending your minutes on edge cases and complexity vs burning them figuring out the approach. If your pattern recognition isn't automatic yet, that's the highest-ROI place to start.
• LLD: practice modeling real-time state sync — the Watch Party problem is essentially Observer over a shared state object. Understand when each design pattern applies, don't just memorize names.
• HLD: be ready to whiteboard your own current project's architecture with no prep. Entity → schema → API → relationships is the spine of most HLD rounds.

Good luck to everyone in the pipeline.

Just finished the Google process — cleared the phone screens, rejected at onsite. Posting the diagnostic because the way I failed is more useful than the fact that I did: I recognized every pattern instantly and still couldn't convert two onsite problems under time. Recognition and implementation-under-pressure are different muscles, and I'd only trained one.

Round 1 — DSA (phone screen)

Array + starting index + value x, operate over rounds:

• Odd round: scan left from current index for the nearest index whose value is exactly double the current → add x there
• Even round: same, scanning right
• Continue while operations are possible

Recognized it immediately as a nearest-element-satisfying-a-condition scan (monotonic-stack family). Wrote brute force, then walked the optimized approach. Interviewer was visibly distracted the whole time — kept glancing away — which threw me. Flagged it to the recruiter; she said feedback was positive anyway.

✅ Cleared.

Round 2 — Googlyness

Best interviewer of the loop, based in Japan, very natural. Collaboration, ownership, conflict, decision-making. Felt like a conversation, no stress games.

✅ Cleared. Recruiter moved me to onsite.

Round 3 — Onsite DSA (prefix search)

Design a Security Monitoring Framework

words = ["abc","abd","abef","xyz"], prefix = "ab"  ->  ["abc","abd","abef"]

Recognized it as a Trie instantly. Couldn't finish a clean implementation in time. Strict interviewer, zero nudges — just watched me struggle through the build.

Round 4 — Onsite DSA (LC 2188, Minimum Time to Finish the Race)

Hard DP. Interviewer split it in two. Got part 1 (per-tire min-cost with the geometric-series cutoff), couldn't land the DP follow-up cleanly under time.

Rejection call a week later.

The actual lesson

My recognition was never the bottleneck — not in R1, not even in the onsite. I knew "monotonic scan," "Trie," "DP transition" within seconds of reading each problem. What I couldn't do was write the involved ones cleanly in the ~25 minutes left after discussion, with a silent interviewer watching. Recognizing a Trie ≠ coding TrieNode + insert + prefix-DFS bug-free under that pressure. Two different skills.

What worked, and where it stopped working:

• Pattern recognition came from drilling on PracHub until the approach surfaced automatically — R1's nearest-double scan I mapped to the monotonic-stack family on sight and never stalled on what to do. For phone-screen and first-onsite difficulty, that recognition speed is genuinely enough to clear the bar on its own, and it's the fastest prep ROI I know.

What I'd add for a Google onsite retry:

• Keep pattern drilling for recognition — still the foundation
• Layer on timed, IDE-based, no-autocomplete implementations of the involved patterns specifically: Trie, segment tree, advanced DP, union-find. 20–30 reps each, time-boxed, no hints, no test runner
• Practice coding in silence with someone playing a non-reactive Google interviewer. Doing it without feedback is its own skill.

Recognition gets you to the right approach fast. At Google onsite, you also have to build it clean while someone watches and says nothing. Train both.

Good luck out there.

Just finished the Google process — cleared the phone screens, rejected at onsite. Posting the diagnostic because the way I failed is more useful than the fact that I did: I recognized every pattern instantly and still couldn't convert two onsite problems under time. Recognition and implementation-under-pressure are different muscles, and I'd only trained one.

Round 1 — DSA (phone screen)

Array + starting index + value x, operate over rounds:

• Odd round: scan left from current index for the nearest index whose value is exactly double the current → add x there
• Even round: same, scanning right
• Continue while operations are possible

Recognized it immediately as a nearest-element-satisfying-a-condition scan (monotonic-stack family). Wrote brute force, then walked the optimized approach. Interviewer was visibly distracted the whole time — kept glancing away — which threw me. Flagged it to the recruiter; she said feedback was positive anyway.

✅ Cleared.

Round 2 — Googlyness

Best interviewer of the loop, based in Japan, very natural. Collaboration, ownership, conflict, decision-making. Felt like a conversation, no stress games.

✅ Cleared. Recruiter moved me to onsite.

Round 3 — Onsite DSA (prefix search)

Design a Security Monitoring Framework

words = ["abc","abd","abef","xyz"], prefix = "ab"  ->  ["abc","abd","abef"]

Recognized it as a Trie instantly. Couldn't finish a clean implementation in time. Strict interviewer, zero nudges — just watched me struggle through the build.

Round 4 — Onsite DSA (LC 2188, Minimum Time to Finish the Race)

Hard DP. Interviewer split it in two. Got part 1 (per-tire min-cost with the geometric-series cutoff), couldn't land the DP follow-up cleanly under time.

Rejection call a week later.

The actual lesson

My recognition was never the bottleneck — not in R1, not even in the onsite. I knew "monotonic scan," "Trie," "DP transition" within seconds of reading each problem. What I couldn't do was write the involved ones cleanly in the ~25 minutes left after discussion, with a silent interviewer watching. Recognizing a Trie ≠ coding TrieNode + insert + prefix-DFS bug-free under that pressure. Two different skills.

What worked, and where it stopped working:

• Pattern recognition came from drilling on PracHub until the approach surfaced automatically — R1's nearest-double scan I mapped to the monotonic-stack family on sight and never stalled on what to do. For phone-screen and first-onsite difficulty, that recognition speed is genuinely enough to clear the bar on its own, and it's the fastest prep ROI I know.

What I'd add for a Google onsite retry:

• Keep pattern drilling for recognition — still the foundation
• Layer on timed, IDE-based, no-autocomplete implementations of the involved patterns specifically: Trie, segment tree, advanced DP, union-find. 20–30 reps each, time-boxed, no hints, no test runner
• Practice coding in silence with someone playing a non-reactive Google interviewer. Doing it without feedback is its own skill.

Recognition gets you to the right approach fast. At Google onsite, you also have to build it clean while someone watches and says nothing. Train both.

Good luck out there.

Just finished the Google process — cleared the phone screens, rejected at onsite. Posting the diagnostic because the way I failed is more useful than the fact that I did: I recognized every pattern instantly and still couldn't convert two onsite problems under time. Recognition and implementation-under-pressure are different muscles, and I'd only trained one.

Round 1 — DSA (phone screen)

Array + starting index + value x, operate over rounds:

• Odd round: scan left from current index for the nearest index whose value is exactly double the current → add x there
• Even round: same, scanning right
• Continue while operations are possible

Recognized it immediately as a nearest-element-satisfying-a-condition scan (monotonic-stack family). Wrote brute force, then walked the optimized approach. Interviewer was visibly distracted the whole time — kept glancing away — which threw me. Flagged it to the recruiter; she said feedback was positive anyway.

✅ Cleared.

Round 2 — Googlyness

Best interviewer of the loop, based in Japan, very natural. Collaboration, ownership, conflict, decision-making. Felt like a conversation, no stress games.

✅ Cleared. Recruiter moved me to onsite.

Round 3 — Onsite DSA (prefix search)

Design a Security Monitoring Framework

words = ["abc","abd","abef","xyz"], prefix = "ab"  ->  ["abc","abd","abef"]

Recognized it as a Trie instantly. Couldn't finish a clean implementation in time. Strict interviewer, zero nudges — just watched me struggle through the build.

Round 4 — Onsite DSA (LC 2188, Minimum Time to Finish the Race)

Hard DP. Interviewer split it in two. Got part 1 (per-tire min-cost with the geometric-series cutoff), couldn't land the DP follow-up cleanly under time.

Rejection call a week later.

The actual lesson

My recognition was never the bottleneck — not in R1, not even in the onsite. I knew "monotonic scan," "Trie," "DP transition" within seconds of reading each problem. What I couldn't do was write the involved ones cleanly in the ~25 minutes left after discussion, with a silent interviewer watching. Recognizing a Trie ≠ coding TrieNode + insert + prefix-DFS bug-free under that pressure. Two different skills.

What worked, and where it stopped working:

• Pattern recognition came from drilling on PracHub until the approach surfaced automatically — R1's nearest-double scan I mapped to the monotonic-stack family on sight and never stalled on what to do. For phone-screen and first-onsite difficulty, that recognition speed is genuinely enough to clear the bar on its own, and it's the fastest prep ROI I know.

What I'd add for a Google onsite retry:

• Keep pattern drilling for recognition — still the foundation
• Layer on timed, IDE-based, no-autocomplete implementations of the involved patterns specifically: Trie, segment tree, advanced DP, union-find. 20–30 reps each, time-boxed, no hints, no test runner
• Practice coding in silence with someone playing a non-reactive Google interviewer. Doing it without feedback is its own skill.

Recognition gets you to the right approach fast. At Google onsite, you also have to build it clean while someone watches and says nothing. Train both.

Good luck out there.

Just finished the Google process — cleared the phone screens, rejected at onsite. Posting the diagnostic because the way I failed is more useful than the fact that I did: I recognized every pattern instantly and still couldn't convert two onsite problems under time. Recognition and implementation-under-pressure are different muscles, and I'd only trained one.

Round 1 — DSA (phone screen)

Array + starting index + value x, operate over rounds:

• Odd round: scan left from current index for the nearest index whose value is exactly double the current → add x there
• Even round: same, scanning right
• Continue while operations are possible

Recognized it immediately as a nearest-element-satisfying-a-condition scan (monotonic-stack family). Wrote brute force, then walked the optimized approach. Interviewer was visibly distracted the whole time — kept glancing away — which threw me. Flagged it to the recruiter; she said feedback was positive anyway.

✅ Cleared.

Round 2 — Googlyness

Best interviewer of the loop, based in Japan, very natural. Collaboration, ownership, conflict, decision-making. Felt like a conversation, no stress games.

✅ Cleared. Recruiter moved me to onsite.

Round 3 — Onsite DSA (prefix search)

Design a Security Monitoring Framework

words = ["abc","abd","abef","xyz"], prefix = "ab"  ->  ["abc","abd","abef"]

Recognized it as a Trie instantly. Couldn't finish a clean implementation in time. Strict interviewer, zero nudges — just watched me struggle through the build.

Round 4 — Onsite DSA (LC 2188, Minimum Time to Finish the Race)

Hard DP. Interviewer split it in two. Got part 1 (per-tire min-cost with the geometric-series cutoff), couldn't land the DP follow-up cleanly under time.

Rejection call a week later.

The actual lesson

My recognition was never the bottleneck — not in R1, not even in the onsite. I knew "monotonic scan," "Trie," "DP transition" within seconds of reading each problem. What I couldn't do was write the involved ones cleanly in the ~25 minutes left after discussion, with a silent interviewer watching. Recognizing a Trie ≠ coding TrieNode + insert + prefix-DFS bug-free under that pressure. Two different skills.

What worked, and where it stopped working:

• Pattern recognition came from drilling on PracHub until the approach surfaced automatically — R1's nearest-double scan I mapped to the monotonic-stack family on sight and never stalled on what to do. For phone-screen and first-onsite difficulty, that recognition speed is genuinely enough to clear the bar on its own, and it's the fastest prep ROI I know.

What I'd add for a Google onsite retry:

• Keep pattern drilling for recognition — still the foundation
• Layer on timed, IDE-based, no-autocomplete implementations of the involved patterns specifically: Trie, segment tree, advanced DP, union-find. 20–30 reps each, time-boxed, no hints, no test runner
• Practice coding in silence with someone playing a non-reactive Google interviewer. Doing it without feedback is its own skill.

Recognition gets you to the right approach fast. At Google onsite, you also have to build it clean while someone watches and says nothing. Train both.

Good luck out there.

Hi everyone — Sharing my Amazon SDE-2 (L5) experience, as precisely as I can remember.

Applied directly through the company portal to every SDE-2 opening I could find. A recruiter reached out with a role and sent the OA.

Round 0 — Online Assessment

Three sections — and the format has changed, so heads up:

• Section 1: 2 questions. One DSA (counting-based). One AI-assisted code repository question — a repo-style codebase (controller / service / repository layers), 6 failing test cases, find and fix the bugs so they pass. An AI assistant was attached but honestly it wasn't much help — couldn't meaningfully navigate or search the codebase. I ended up finding the issues myself.
• Section 2: Order-of-decisions reasoning — given a project state, sequence the right steps (planning, architecture, POC, API dev, etc.) with technical justification.
• Section 3: Behavioural — "most like me / least like me" style.

Solved all test cases on the DSA, 5/6 on the AI-assisted repo question. Cleared it — recruiter confirmed May 5 and said the first 2 rounds would gate the rest.

Took some time to prep the loops properly.

Round 1 — DSA + LP

Straight into DSA after intros:

• Aggressive Cows (binary-search-on-answer)
• Find Median from a Data Stream (two-heaps)

Explained brute force → optimized for each, with complexity. Solved both quickly, so we had extra time — interviewer dug into hashmap and heap internals afterward.

LP:

• A time you had to debug a difficult issue — what could you have done better?
• A time you gave a simple solution to a complex problem.

Honest note: my LPs here were shaky. I wasn't well-prepared for behavioural going into R1 and I could feel it.

HR verdict (next day): Inclined. They scheduled the HLD round.

Round 2 — LLD / Maintainable Code + LP (May 25), SDE-2 interviewer

Debug Watch List Movie Operations:

• You are given a full-stack Movie DB application. Users can log in, create, update, and delete watch lists, and add or remove movies from a watch list.

Several unit tests are failing around watch-list movie operations. Your job is to debug and fix the backend logic so that all of the listed scenarios behave correctly, with the right persistence and the right HTTP responses. This is a debugging exercise: the data model and routing already exist — focus on correcting the handler logic rather than redesigning the system.

Used Strategy + Factory + Singleton. Then follow-ups on extensibility.

LLD tip: once your base design is clean, proactively bring up fault tolerance, resiliency, and scalability. It adds maturity and the interviewer clearly registered it.

LP:

• Something you recently learned and applied at work
• How you measure the success metrics of a learning journey

Best round of my loop — LPs were solid by now.

HR (next day): Inclined.

Round 3 — HLD + LP (May 26), Engineering Manager

Problem statement, in full: "Design Netflix." That's it. Had to derive requirements myself and diagram on BlueSpace (Excalidraw-style), covering availability, scalability, fault tolerance, and the trade-offs of my approach. Interviewer interjected with constraints to fold in.

Good discussion on movie search via a reverse-index store like OpenSearch, plus a CDC pipeline for keeping it in sync.

LP:

• A time you had a conflict with seniors and turned out right
• A time you got harsh feedback from your manager and how you incorporated it

Felt strong. Interviewer seemed satisfied.

HR (same day): Inclined. Bar raiser scheduled.

Round 4 — Bar Raiser, Principal TPM

Mostly behavioural/leadership, with one DSA:

• Unique permutations of a string (e.g. "xxyy" → each distinct arrangement once). Solved with frequency-map + backtracking to prune duplicates.

Then 2 LP questions with heavy follow-ups:

• A time you learned something quickly and applied it
• A time you delivered under a tight deadline

I had solid stories + metrics ready, and the interviewer drilled hard into how the metrics were actually gathered. Felt only okay — the bar raiser gave zero signal, which made me nervous.

HR (same day): Selected. Offer 2 days later.

(Will add detailed comp soon.)

Prep notes — what actually moved the needle

• PracHub was the single most valuable thing in my DSA prep. The reason I cleared the coding portions fast enough to leave time for the deep-dives — heap/hashmap internals in R1, the bar-raiser follow-ups — is that I'd drilled the underlying patterns there until recognition was instant. Aggressive Cows → binary-search-on-answer, Median-in-a-stream → two-heaps, unique permutations → backtracking with frequency pruning: I didn't derive any of those cold, because I'd worked enough variants on PracHub that the approach surfaced in seconds. That speed is what bought me the room to discuss trade-offs and internals — which is where SDE-2 candidates actually get separated. If your pattern recognition isn't automatic yet, that's the highest-leverage place to put your time.
• LP was my weak spot and I felt it in R1. Fixed it hard before R2: 2–3 real STAR stories per principle with genuine success metrics. By the bar raiser I could survive deep follow-ups on how metrics were gathered. Don't treat LP as the soft part — at Amazon it's half the loop.
• OA's AI-assisted bug-fix round: practice navigating an unfamiliar codebase in a real framework. The provided AI won't save you.

Takeaways

• Solve DSA fast enough to leave time for the internals discussion — that's where the points are.
• LPs are not a formality. Especially the bar raiser.
• For LLD, layer resiliency/scalability on top of a clean design.
• The bar raiser giving no signal is normal. Don't read into it.

All the best to everyone prepping. 🙌

Hi everyone — Sharing my Amazon SDE-2 (L5) experience, as precisely as I can remember.

Applied directly through the company portal to every SDE-2 opening I could find. A recruiter reached out with a role and sent the OA.

Round 0 — Online Assessment

Three sections — and the format has changed, so heads up:

• Section 1: 2 questions. One DSA (counting-based). One AI-assisted code repository question — a repo-style codebase (controller / service / repository layers), 6 failing test cases, find and fix the bugs so they pass. An AI assistant was attached but honestly it wasn't much help — couldn't meaningfully navigate or search the codebase. I ended up finding the issues myself.
• Section 2: Order-of-decisions reasoning — given a project state, sequence the right steps (planning, architecture, POC, API dev, etc.) with technical justification.
• Section 3: Behavioural — "most like me / least like me" style.

Solved all test cases on the DSA, 5/6 on the AI-assisted repo question. Cleared it — recruiter confirmed May 5 and said the first 2 rounds would gate the rest.

Took some time to prep the loops properly.

Round 1 — DSA + LP

Straight into DSA after intros:

• Aggressive Cows (binary-search-on-answer)
• Find Median from a Data Stream (two-heaps)

Explained brute force → optimized for each, with complexity. Solved both quickly, so we had extra time — interviewer dug into hashmap and heap internals afterward.

LP:

• A time you had to debug a difficult issue — what could you have done better?
• A time you gave a simple solution to a complex problem.

Honest note: my LPs here were shaky. I wasn't well-prepared for behavioural going into R1 and I could feel it.

HR verdict (next day): Inclined. They scheduled the HLD round.

Round 2 — LLD / Maintainable Code + LP (May 25), SDE-2 interviewer

Debug Watch List Movie Operations:

• You are given a full-stack Movie DB application. Users can log in, create, update, and delete watch lists, and add or remove movies from a watch list.

Several unit tests are failing around watch-list movie operations. Your job is to debug and fix the backend logic so that all of the listed scenarios behave correctly, with the right persistence and the right HTTP responses. This is a debugging exercise: the data model and routing already exist — focus on correcting the handler logic rather than redesigning the system.

Used Strategy + Factory + Singleton. Then follow-ups on extensibility.

LLD tip: once your base design is clean, proactively bring up fault tolerance, resiliency, and scalability. It adds maturity and the interviewer clearly registered it.

LP:

• Something you recently learned and applied at work
• How you measure the success metrics of a learning journey

Best round of my loop — LPs were solid by now.

HR (next day): Inclined.

Round 3 — HLD + LP (May 26), Engineering Manager

Problem statement, in full: "Design Netflix." That's it. Had to derive requirements myself and diagram on BlueSpace (Excalidraw-style), covering availability, scalability, fault tolerance, and the trade-offs of my approach. Interviewer interjected with constraints to fold in.

Good discussion on movie search via a reverse-index store like OpenSearch, plus a CDC pipeline for keeping it in sync.

LP:

• A time you had a conflict with seniors and turned out right
• A time you got harsh feedback from your manager and how you incorporated it

Felt strong. Interviewer seemed satisfied.

HR (same day): Inclined. Bar raiser scheduled.

Round 4 — Bar Raiser, Principal TPM

Mostly behavioural/leadership, with one DSA:

• Unique permutations of a string (e.g. "xxyy" → each distinct arrangement once). Solved with frequency-map + backtracking to prune duplicates.

Then 2 LP questions with heavy follow-ups:

• A time you learned something quickly and applied it
• A time you delivered under a tight deadline

I had solid stories + metrics ready, and the interviewer drilled hard into how the metrics were actually gathered. Felt only okay — the bar raiser gave zero signal, which made me nervous.

HR (same day): Selected. Offer 2 days later.

(Will add detailed comp soon.)

Prep notes — what actually moved the needle

• PracHub was the single most valuable thing in my DSA prep. The reason I cleared the coding portions fast enough to leave time for the deep-dives — heap/hashmap internals in R1, the bar-raiser follow-ups — is that I'd drilled the underlying patterns there until recognition was instant. Aggressive Cows → binary-search-on-answer, Median-in-a-stream → two-heaps, unique permutations → backtracking with frequency pruning: I didn't derive any of those cold, because I'd worked enough variants on PracHub that the approach surfaced in seconds. That speed is what bought me the room to discuss trade-offs and internals — which is where SDE-2 candidates actually get separated. If your pattern recognition isn't automatic yet, that's the highest-leverage place to put your time.
• LP was my weak spot and I felt it in R1. Fixed it hard before R2: 2–3 real STAR stories per principle with genuine success metrics. By the bar raiser I could survive deep follow-ups on how metrics were gathered. Don't treat LP as the soft part — at Amazon it's half the loop.
• OA's AI-assisted bug-fix round: practice navigating an unfamiliar codebase in a real framework. The provided AI won't save you.

Takeaways

• Solve DSA fast enough to leave time for the internals discussion — that's where the points are.
• LPs are not a formality. Especially the bar raiser.
• For LLD, layer resiliency/scalability on top of a clean design.
• The bar raiser giving no signal is normal. Don't read into it.

All the best to everyone prepping. 🙌

Hi everyone — Sharing my Amazon SDE-2 (L5) experience, as precisely as I can remember.

Applied directly through the company portal to every SDE-2 opening I could find. A recruiter reached out with a role and sent the OA.

Round 0 — Online Assessment

Three sections — and the format has changed, so heads up:

• Section 1: 2 questions. One DSA (counting-based). One AI-assisted code repository question — a repo-style codebase (controller / service / repository layers), 6 failing test cases, find and fix the bugs so they pass. An AI assistant was attached but honestly it wasn't much help — couldn't meaningfully navigate or search the codebase. I ended up finding the issues myself.
• Section 2: Order-of-decisions reasoning — given a project state, sequence the right steps (planning, architecture, POC, API dev, etc.) with technical justification.
• Section 3: Behavioural — "most like me / least like me" style.

Solved all test cases on the DSA, 5/6 on the AI-assisted repo question. Cleared it — recruiter confirmed May 5 and said the first 2 rounds would gate the rest.

Took some time to prep the loops properly.

Round 1 — DSA + LP

Straight into DSA after intros:

• Aggressive Cows (binary-search-on-answer)
• Find Median from a Data Stream (two-heaps)

Explained brute force → optimized for each, with complexity. Solved both quickly, so we had extra time — interviewer dug into hashmap and heap internals afterward.

LP:

• A time you had to debug a difficult issue — what could you have done better?
• A time you gave a simple solution to a complex problem.

Honest note: my LPs here were shaky. I wasn't well-prepared for behavioural going into R1 and I could feel it.

HR verdict (next day): Inclined. They scheduled the HLD round.

Round 2 — LLD / Maintainable Code + LP (May 25), SDE-2 interviewer

Debug Watch List Movie Operations:

• You are given a full-stack Movie DB application. Users can log in, create, update, and delete watch lists, and add or remove movies from a watch list.

Several unit tests are failing around watch-list movie operations. Your job is to debug and fix the backend logic so that all of the listed scenarios behave correctly, with the right persistence and the right HTTP responses. This is a debugging exercise: the data model and routing already exist — focus on correcting the handler logic rather than redesigning the system.

Used Strategy + Factory + Singleton. Then follow-ups on extensibility.

LLD tip: once your base design is clean, proactively bring up fault tolerance, resiliency, and scalability. It adds maturity and the interviewer clearly registered it.

LP:

• Something you recently learned and applied at work
• How you measure the success metrics of a learning journey

Best round of my loop — LPs were solid by now.

HR (next day): Inclined.

Round 3 — HLD + LP (May 26), Engineering Manager

Problem statement, in full: "Design Netflix." That's it. Had to derive requirements myself and diagram on BlueSpace (Excalidraw-style), covering availability, scalability, fault tolerance, and the trade-offs of my approach. Interviewer interjected with constraints to fold in.

Good discussion on movie search via a reverse-index store like OpenSearch, plus a CDC pipeline for keeping it in sync.

LP:

• A time you had a conflict with seniors and turned out right
• A time you got harsh feedback from your manager and how you incorporated it

Felt strong. Interviewer seemed satisfied.

HR (same day): Inclined. Bar raiser scheduled.

Round 4 — Bar Raiser, Principal TPM

Mostly behavioural/leadership, with one DSA:

• Unique permutations of a string (e.g. "xxyy" → each distinct arrangement once). Solved with frequency-map + backtracking to prune duplicates.

Then 2 LP questions with heavy follow-ups:

• A time you learned something quickly and applied it
• A time you delivered under a tight deadline

I had solid stories + metrics ready, and the interviewer drilled hard into how the metrics were actually gathered. Felt only okay — the bar raiser gave zero signal, which made me nervous.

HR (same day): Selected. Offer 2 days later.

(Will add detailed comp soon.)

Prep notes — what actually moved the needle

• PracHub was the single most valuable thing in my DSA prep. The reason I cleared the coding portions fast enough to leave time for the deep-dives — heap/hashmap internals in R1, the bar-raiser follow-ups — is that I'd drilled the underlying patterns there until recognition was instant. Aggressive Cows → binary-search-on-answer, Median-in-a-stream → two-heaps, unique permutations → backtracking with frequency pruning: I didn't derive any of those cold, because I'd worked enough variants on PracHub that the approach surfaced in seconds. That speed is what bought me the room to discuss trade-offs and internals — which is where SDE-2 candidates actually get separated. If your pattern recognition isn't automatic yet, that's the highest-leverage place to put your time.
• LP was my weak spot and I felt it in R1. Fixed it hard before R2: 2–3 real STAR stories per principle with genuine success metrics. By the bar raiser I could survive deep follow-ups on how metrics were gathered. Don't treat LP as the soft part — at Amazon it's half the loop.
• OA's AI-assisted bug-fix round: practice navigating an unfamiliar codebase in a real framework. The provided AI won't save you.

Takeaways

• Solve DSA fast enough to leave time for the internals discussion — that's where the points are.
• LPs are not a formality. Especially the bar raiser.
• For LLD, layer resiliency/scalability on top of a clean design.
• The bar raiser giving no signal is normal. Don't read into it.

All the best to everyone prepping. 🙌

Hi everyone — Sharing my Amazon SDE-2 (L5) experience, as precisely as I can remember.

Applied directly through the company portal to every SDE-2 opening I could find. A recruiter reached out with a role and sent the OA.

Round 0 — Online Assessment

Three sections — and the format has changed, so heads up:

• Section 1: 2 questions. One DSA (counting-based). One AI-assisted code repository question — a repo-style codebase (controller / service / repository layers), 6 failing test cases, find and fix the bugs so they pass. An AI assistant was attached but honestly it wasn't much help — couldn't meaningfully navigate or search the codebase. I ended up finding the issues myself.
• Section 2: Order-of-decisions reasoning — given a project state, sequence the right steps (planning, architecture, POC, API dev, etc.) with technical justification.
• Section 3: Behavioural — "most like me / least like me" style.

Solved all test cases on the DSA, 5/6 on the AI-assisted repo question. Cleared it — recruiter confirmed May 5 and said the first 2 rounds would gate the rest.

Took some time to prep the loops properly.

Round 1 — DSA + LP (May 20), SDE-2 interviewer

Straight into DSA after intros:

• Aggressive Cows (binary-search-on-answer)
• Find Median from a Data Stream (two-heaps)

Explained brute force → optimized for each, with complexity. Solved both quickly, so we had extra time — interviewer dug into hashmap and heap internals afterward.

LP:

• A time you had to debug a difficult issue — what could you have done better?
• A time you gave a simple solution to a complex problem.

Honest note: my LPs here were shaky. I wasn't well-prepared for behavioural going into R1 and I could feel it.

HR verdict (next day): Inclined. They scheduled the HLD round.

Round 2 — LLD / Maintainable Code + LP (May 25), SDE-2 interviewer

Debug Watch List Movie Operations:

• You are given a full-stack Movie DB application. Users can log in, create, update, and delete watch lists, and add or remove movies from a watch list.

Several unit tests are failing around watch-list movie operations. Your job is to debug and fix the backend logic so that all of the listed scenarios behave correctly, with the right persistence and the right HTTP responses. This is a debugging exercise: the data model and routing already exist — focus on correcting the handler logic rather than redesigning the system.

Used Strategy + Factory + Singleton. Then follow-ups on extensibility.

LLD tip: once your base design is clean, proactively bring up fault tolerance, resiliency, and scalability. It adds maturity and the interviewer clearly registered it.

LP:

• Something you recently learned and applied at work
• How you measure the success metrics of a learning journey

Best round of my loop — LPs were solid by now.

HR (next day): Inclined.

Round 3 — HLD + LP (May 26), Engineering Manager

Problem statement, in full: "Design Netflix." That's it. Had to derive requirements myself and diagram on BlueSpace (Excalidraw-style), covering availability, scalability, fault tolerance, and the trade-offs of my approach. Interviewer interjected with constraints to fold in.

Good discussion on movie search via a reverse-index store like OpenSearch, plus a CDC pipeline for keeping it in sync.

LP:

• A time you had a conflict with seniors and turned out right
• A time you got harsh feedback from your manager and how you incorporated it

Felt strong. Interviewer seemed satisfied.

HR (same day): Inclined. Bar raiser scheduled.

Round 4 — Bar Raiser, Principal TPM

Mostly behavioural/leadership, with one DSA:

• Unique permutations of a string (e.g. "xxyy" → each distinct arrangement once). Solved with frequency-map + backtracking to prune duplicates.

Then 2 LP questions with heavy follow-ups:

• A time you learned something quickly and applied it
• A time you delivered under a tight deadline

I had solid stories + metrics ready, and the interviewer drilled hard into how the metrics were actually gathered. Felt only okay — the bar raiser gave zero signal, which made me nervous.

HR (same day): Selected. Offer 2 days later.

(Will add detailed comp soon.)

Prep notes — what actually moved the needle

• PracHub was the single most valuable thing in my DSA prep. The reason I cleared the coding portions fast enough to leave time for the deep-dives — heap/hashmap internals in R1, the bar-raiser follow-ups — is that I'd drilled the underlying patterns there until recognition was instant. Aggressive Cows → binary-search-on-answer, Median-in-a-stream → two-heaps, unique permutations → backtracking with frequency pruning: I didn't derive any of those cold, because I'd worked enough variants on PracHub that the approach surfaced in seconds. That speed is what bought me the room to discuss trade-offs and internals — which is where SDE-2 candidates actually get separated. If your pattern recognition isn't automatic yet, that's the highest-leverage place to put your time.
• LP was my weak spot and I felt it in R1. Fixed it hard before R2: 2–3 real STAR stories per principle with genuine success metrics. By the bar raiser I could survive deep follow-ups on how metrics were gathered. Don't treat LP as the soft part — at Amazon it's half the loop.
• OA's AI-assisted bug-fix round: practice navigating an unfamiliar codebase in a real framework. The provided AI won't save you.

Takeaways

• Solve DSA fast enough to leave time for the internals discussion — that's where the points are.
• LPs are not a formality. Especially the bar raiser.
• For LLD, layer resiliency/scalability on top of a clean design.
• The bar raiser giving no signal is normal. Don't read into it.

All the best to everyone prepping. 🙌

Gave the Amazon SDE-2 loop last month. Applied directly on the career portal — OA next day, done same day, interview call the day after, R1 a week later. Process was fast.

Posting because I'm genuinely confused about the reject, and maybe folks here who've cleared SDE-2 recently can tell me where I went wrong.

OA

• 2 Typical Amazon SWE Question
• A full-stack bug-fix question — pick your backend framework, get a codebase + list of bugs, find and fix. They gave an AI assistant for it but honestly it was useless, couldn't even help me navigate or search the codebase
• Some behavioural/design-choice MCQ-type questions

Round 1 — DSA
2 easy–medium problems, but they wanted real depth on each.

LC 16 – 3Sum Closest (n ≤ 10³). Gave 3 full approaches with complexity + dry run for each:

• Brute force O(n³)
• Binary search O(n² log n)
• Two pointers O(n²)

LC 305 – Number of Islands II. Gave 2 approaches:

• Brute force O(n²·q)
• Union-Find (DSU) O(q + n²)

Then the usual "tell me about a time you…" LP questions.

Verdict: Rejected

Gave the Amazon SDE-2 loop last month. Applied directly on the career portal — OA next day, done same day, interview call the day after, R1 a week later. Process was fast.

Posting because I'm genuinely confused about the reject, and maybe folks here who've cleared SDE-2 recently can tell me where I went wrong.

OA

• 2 Typical Amazon SWE Question
• A full-stack bug-fix question — pick your backend framework, get a codebase + list of bugs, find and fix. They gave an AI assistant for it but honestly it was useless, couldn't even help me navigate or search the codebase
• Some behavioural/design-choice MCQ-type questions

Round 1 — DSA
2 easy–medium problems, but they wanted real depth on each.

LC 16 – 3Sum Closest (n ≤ 10³). Gave 3 full approaches with complexity + dry run for each:

• Brute force O(n³)
• Binary search O(n² log n)
• Two pointers O(n²)

LC 305 – Number of Islands II. Gave 2 approaches:

• Brute force O(n²·q)
• Union-Find (DSU) O(q + n²)

Then the usual "tell me about a time you…" LP questions.

Verdict: Rejected

Gave the Amazon SDE-2 loop last month. Applied directly on the career portal — OA next day, done same day, interview call the day after, R1 a week later. Process was fast.

Posting because I'm genuinely confused about the reject, and maybe folks here who've cleared SDE-2 recently can tell me where I went wrong.

OA

• 2 Typical Amazon SWE Question
• A full-stack bug-fix question — pick your backend framework, get a codebase + list of bugs, find and fix. They gave an AI assistant for it but honestly it was useless, couldn't even help me navigate or search the codebase
• Some behavioural/design-choice MCQ-type questions

Round 1 — DSA
2 easy–medium problems, but they wanted real depth on each.

LC 16 – 3Sum Closest (n ≤ 10³). Gave 3 full approaches with complexity + dry run for each:

• Brute force O(n³)
• Binary search O(n² log n)
• Two pointers O(n²)

LC 305 – Number of Islands II. Gave 2 approaches:

• Brute force O(n²·q)
• Union-Find (DSU) O(q + n²)

Then the usual "tell me about a time you…" LP questions.

Verdict: Rejected

Gave the Amazon SDE-2 loop last month. Applied directly on the career portal — OA next day, done same day, interview call the day after, R1 a week later. Process was fast.

Posting because I'm genuinely confused about the reject, and maybe folks here who've cleared SDE-2 recently can tell me where I went wrong.

OA

• 2 Typical Amazon SWE Question
• A full-stack bug-fix question — pick your backend framework, get a codebase + list of bugs, find and fix. They gave an AI assistant for it but honestly it was useless, couldn't even help me navigate or search the codebase
• Some behavioural/design-choice MCQ-type questions

Round 1 — DSA
2 easy–medium problems, but they wanted real depth on each.

LC 16 – 3Sum Closest (n ≤ 10³). Gave 3 full approaches with complexity + dry run for each:

• Brute force O(n³)
• Binary search O(n² log n)
• Two pointers O(n²)

LC 305 – Number of Islands II. Gave 2 approaches:

• Brute force O(n²·q)
• Union-Find (DSU) O(q + n²)

Then the usual "tell me about a time you…" LP questions.

Verdict: Rejected