Amazon | SDE-2 | Hyderabad (In-person + Virtual)

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SDE-2HyderabadOngoing
August 23, 202521 reads

Summary

I recently interviewed for an SDE-2 role at Amazon, experiencing a mix of in-person system design and virtual coding/hiring manager rounds. The process is currently stalled due to an unfulfilled Bar Raiser round, with no recent communication from the recruiter.

Full Experience

I recently had an interview experience for an SDE-2 role at Amazon. Although I haven't received any official communication regarding the outcome yet, I wanted to share the details of my rounds, hoping they might assist others in their preparation.

Timeline & Process:

The initial screening rounds were fairly standard.

Online Assessment:

I don't precisely recall the questions from the Online Assessment.

Round 1 & 2: System Design (LLD + HLD) - July 29th (In-person)

This was a full day on-site, featuring back-to-back design rounds, each lasting 60 minutes.

Round 1: Low-Level Design (LLD)

The problem presented was to Design a Movie Ticket Booking System. The focus was heavily on object-oriented principles. I was tasked with defining the main classes like User, Movie, Cinema, Booking, and Seat, establishing their relationships, and outlining the core APIs. We delved into a deep discussion on how to handle concurrency, for instance, when two users attempt to book the same seat simultaneously, and the specifics of the database schema design. This round concluded with about 15 minutes of behavioral questions related to Amazon's leadership principles, specifically "Ownership" and "Bias for Action," drawing from my past projects.

Round 2: High-Level Design (HLD)

For this round, I was asked to Design a Trending Service for the Top K products on an e-commerce homepage, similar to what Amazon itself might use. The core expectation here was to address scale and availability. I had to design the entire system, from data ingestion (considering product views, clicks, and purchases) to the final API responsible for serving the top K trending products. Key topics we explored included stream processing using technologies like Kafka/Kinesis, real-time data aggregation techniques, various caching strategies (mentioning Redis and CDN), appropriate database choices (like using Redis Sorted Sets for a leaderboard functionality), and methods to avoid bottlenecks while ensuring low latency. Similar to the previous round, the last 15 minutes were dedicated to behavioral questions, this time focusing on "Dealing with Ambiguity" and "Customer Obsession."

Round 3: Hiring Manager Round - (Online)

This was a 60-minute virtual call with the potential hiring manager. I was asked two coding questions:

At the end, I had the opportunity to ask my own questions about the team's culture, current challenges, and their roadmap for the upcoming year.

Round 4: The Bar Raiser (BR) Saga - August 4th onwards

This part of the process took an unexpected turn. My Bar Raiser round was initially scheduled for August 4th, intended to be another 60-minute session. However, the interviewer was a no-show. It's been almost a month since that scheduled round. The recruiter had been rescheduling it weekly for a while, but recently, they have stopped replying to my follow-up emails, leaving the status quite uncertain.

Interview Questions (8)

Q1
Design a Movie Ticket Booking System (LLD)
System Design

Design a Movie Ticket Booking System focusing on object-oriented principles. Define main classes such as User, Movie, Cinema, Booking, Seat, their relationships, and core APIs. Discuss handling concurrency (e.g., two users trying to book the same seat simultaneously) and database schema design.

Q2
Behavioral: Ownership
Behavioral

Behavioral questions focused on the leadership principle 'Ownership', asking about past projects and experiences related to taking responsibility and driving results.

Q3
Behavioral: Bias for Action
Behavioral

Behavioral questions focused on the leadership principle 'Bias for Action', inquiring about instances where I took swift, decisive action to achieve outcomes.

Q4
Design a Trending Service for Top K Products (HLD)
System Design

Design a highly scalable and available Trending Service for the Top K products on an e-commerce homepage. The design should cover data ingestion (product views, clicks, purchases) to the final API that serves the top K products. Key discussion points included stream processing (Kafka/Kinesis), real-time data aggregation, caching strategies (Redis, CDN), database choice (e.g., Redis Sorted Sets for a leaderboard), avoiding bottlenecks, and ensuring low latency.

Q5
Behavioral: Dealing with Ambiguity
Behavioral

Behavioral questions centered on the leadership principle 'Dealing with Ambiguity', exploring how I've navigated unclear situations or changing requirements.

Q6
Behavioral: Customer Obsession
Behavioral

Behavioral questions focused on the leadership principle 'Customer Obsession', asking about experiences where I prioritized and advocated for customer needs.

Q7
Binary Tree Level Order Traversal (Variation)
Data Structures & AlgorithmsMedium

A variation of the standard Binary Tree Level Order Traversal problem.

Q8
Number of Pairs of Interchangeable Rectangles
Data Structures & AlgorithmsMedium

Solve the problem of finding the number of pairs of interchangeable rectangles.

Preparation Tips

Based on this experience, I believe future candidates should prepare thoroughly, especially for the system design rounds. These really test your ability to think on your feet and discuss complex architectures under pressure. For the coding rounds, practicing problems from platforms like LeetCode, particularly those that involve common data structures and algorithms, is crucial. Being prepared to discuss behavioral scenarios linked to Amazon's leadership principles is also vital, as these were a consistent part of each round.

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