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Amazon interview notes, page 26 of 159

FAANG / Big Tech

Most of these Amazon write-ups come from Software Engineers (1,092), then Data Scientists (182) and Product Managers (165). The most reported rounds are the technical phone screen (618), the behavioral / leadership round (309), the online assessment (228) and the system design round (159).

1581 interview notes · updated Oct 2026

Amazon·Software Engineer·Onsite - Coding / Algorithms

Apr 2026
Amazon SDE interview with a behavioral opener and a string rearrangement coding problem. Never got to a clean working solution, and now I'm sitting here wondering if that tanked the whole round.
  • Tell me about a time you delivered a project under significant time pressure.
  • Given a string, rearrange its characters so no two adjacent characters are the same. Return the result, or an empty string if it's impossible.

“Had a real story ready for this one.”

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Amazon·Data Scientist·Technical Phone Screen

Apr 2026
Got a stats question at Amazon that felt deceptively simple but I definitely fumbled parts of the explanation.
  • How do you determine the required sample size given a desired statistical power?

“I knew the general idea, effect size, significance level, power, but when I tried to walk through it out loud I got tangled up in the direction of the relationship between sample size and power.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Amazon behavioral round for a software engineer role. The interviewer dug into a tight deadline story pretty aggressively, peeling back each layer until I was basically defending every decision I made on the project.
  • Tell me about a time you worked under a tight deadline.

“I shared a project story and thought I was done, but then they asked exactly what my contribution was, and then how I figured out priorities when there wasn't enough time or people to do everything.”

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Amazon·Product Manager·Onsite - Cross-functional / Panel

Apr 2026
Amazon PM interview, one question that sounds straightforward until you're actually in it. The whole thing is about communication strategy across three different audiences for the same initiative, which is trickier to articulate on the spot than it looks on paper.
  • Your VP launches an initiative to improve safety, boost efficiency, and reduce costs. How do you adapt your communication and change-management approach for three different groups: your peer managers, the managers who report to you, and front-line employees?

“I went in thinking this was a standard stakeholder question and kind of treated all three audiences similarly at first, which was the wrong move.”

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Amazon·Software Engineer·Onsite - Coding / Algorithms

Apr 2026
Amazon SWE coding round, one question the whole session: weighted random index. Felt manageable but the follow-up about efficiency under repeated calls is where things got interesting.
  • Design a data structure that takes an array of weights and supports a pickIndex() method that returns a random index with probability proportional to its weight. It needs to handle up to 200k elements and up to 200k calls efficiently.

“My first instinct was just to build a giant array repeating each index by its weight and sample from it.”

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Amazon·Data Scientist·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round at Amazon for a Data Scientist role. One question, heavy on the leadership principles angle, and it was basically the whole conversation.
  • Tell me about a time you had to deliver a data science solution under a very tight deadline. How did you decide what to prioritize, get stakeholders on board, and handle the risks involved?

“I had a decent story ready but I rambled too much on the setup and ran out of time before I could land the actual impact numbers, which is obviously the part they care about most.”

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Amazon·Data Scientist·Technical Phone Screen

Apr 2026
Amazon DS interview with a classic metric drop scenario. One question, but it had a lot of moving parts and I felt like I was juggling too many things at once.
  • A key product metric suddenly drops. Walk through how you'd diagnose the cause, what analyses you'd run, and how you'd design an experiment to confirm your main hypothesis. What primary and guardrail metrics would you track?

“I started with segmentation, which was fine, but I fumbled when they pushed on the metric hierarchy piece.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Amazon system design round for a software engineer role. The question was about building a task management system, which sounds straightforward until you realize they want you to cover basically everything: data modeling, APIs, storage choices, thread safety, ID generation, performance, and testing. A lot of ground for one question.
  • Design a task management system that supports adding tasks with unique IDs, marking tasks complete, retrieving incomplete and completed tasks, and fetching a task by ID. Cover the data model, core APIs, storage approach, thread safety, ID generation, performance, and testing strategy.

“I started with the data model, which felt safe, then moved into the API surface.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Amazon solutions architect interview, one system design question about building an e-commerce platform. Pretty open-ended, which I wasn't fully prepared for.
  • Design an e-commerce website from scratch.

“Scope creep killed me here.”

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Amazon·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
PM interview at Amazon focused on a fulfillment operations scenario. One question, fairly meaty, sat at the intersection of product strategy and customer-facing recommendations.
  • You're a PM for Amazon Fulfillment and need to reduce warehouse space usage by optimizing SKUs. How would you design a recommendation system on Amazon Prime that surfaces similar products to customers?

“The warehouse angle threw me a bit.”

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