Amazon | SDE2 | Feb 2026 [Selected]
Anonymous User
1889
Mar 28, 2026
Interview

  • Status: SDE2 at Mid-sized Tech

  • Experience: 4 Years

  • Position: SDE2 (L5) at Amazon

  • Date: February 2026

Online Assessment (OA)

Two coding questions + Work Style Simulation.

  1. Question 1: Variation of Merge Intervals.

  2. Question 2: Graph/Dijkstra based.

  3. Simulation: Focus heavily on Ownership and Bias for Action. Don't just pick the "safe" answer; pick the one that delivers for the customer.

Virtual Onsite (4 Rounds)

Round 1: Data Structures & Algorithms

  • Leadership Principles (LP): Customer Obsession and Ownership.

  • Technical: LeetCode 1094 (Car Pooling) variant.

  • Details: After solving with a TreeMap (), the interviewer pushed for an solution using a difference array. We then discussed how to scale this if the "trips" data was stored in a distributed DB.

Round 2: System Design (HLD)

  • LP: Learn and Be Curious and Dive Deep.

  • Technical: Design a Real-Time Error Log Monitoring System.

  • Details:

    • Requirements: Handle 1M+ writes/sec, sub-second alerting.

    • Architecture: Used Kafka for the ingestion layer, Flink for windowed aggregation, and Elasticsearch for querying.

    • Deep Dive: We spent 15 minutes on backpressure—what happens when the consumer can't keep up with the log spikes?

Round 3: Object-Oriented Design (LLD)

  • LP: Bias for Action and Disagree and Commit.

  • Technical: Design a Vending Machine Leasing System.

  • Details: Focused on the relationship between VendingMachine, LeaseAgreement, and PaymentStrategy.

  • Key: Used the State Pattern to handle machine conditions (Idle, Out of Stock, Maintenance). The interviewer looked for clean interfaces and extensibility.

Round 4: The Bar Raiser

  • LP: Insist on the Highest Standards and Deliver Results.

  • Technical: Distributed Rate Limiter.

  • Details: * Started with the Token Bucket algorithm logic.

    • Moved into the implementation: How to handle concurrency using Redis Lua scripts to ensure atomicity.

    • The LP part was intense; they kept asking for specific data points and metrics for every "Result" I mentioned.

Result: Offer.

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