Amazon Interview Questions — Page 69

Amazon·Data Scientist·Onsite - Coding / Algorithms

May 2026

Final round for a Data Scientist role at Amazon, and they threw a classic hard algorithm problem at me. Not what I was expecting given the role, but apparently they do this.

Implement a function to merge k sorted linked lists into one sorted list, and walk through the time and space complexity of your approach.

“I went straight for the min-heap solution because it felt cleaner to explain.”

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Amazon·Software Engineer·Online Assessment (OA)

May 2026

Took the Amazon OA recently. DSA portion went fine but the AI-assisted Spring Boot bug fix section was rough, only cleared 1 out of 6 test cases and now I'm wondering if anyone's actually gotten a clean sweep on that part.

In the Spring Boot bug fix section of the OA, can you identify and fix the bugs in the provided codebase to pass all test cases?

“Got through the DSA stuff okay but this section completely humbled me.”

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Amazon·Data Scientist·Technical Phone Screen

May 2026

Amazon Data Scientist technical screen, heavy pandas and data engineering focus. The main problem was a subscription-revenue attribution question that looked like a pandas exercise but quickly turned into a system design conversation about scaling to 100M events.

Given an events table and a subscriptions table, compute per-user active subscription days and purchase revenue attributed only to periods when the user had an active subscription, for a specific month. Also flag purchases that fall outside any active subscription window.
How would you merge overlapping or back-to-back subscription intervals into minimal disjoint half-open intervals before attributing revenue?
How would you scale this subscription-revenue attribution pipeline to handle 100 million events with limited RAM? What specific techniques would you use?
Output two separate DataFrames: one with user-month aggregates (active days, subscribed revenue, out-of-window purchase count) and one anomaly log with a reason column indicating whether a purchase was outside a subscription window or flagged due to a fixed overlap. How do you structure and populate both?

“This was the core of the whole interview.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

May 2026

Amazon system design round for a software engineering role. The whole thing was one big design question about memory management and it went deep fast, covering OS internals, concurrency, multi-tenancy, and ops concerns all in one shot.

Design an in-process memory usage monitor that switches an application between NORMAL and DEGRADED modes based on configurable thresholds, with hysteresis to prevent flapping between states.
How would you design the API surface for this system, specifically setThresholds, getState, and registerCallbacks, and what actions should trigger on mode transitions like cache eviction, request rejection, or batch slowdown?
Compare different approaches to sampling memory usage across Linux and macOS: polling process RSS, using OS memory-pressure notifications, and reading container or cgroup signals. What are the tradeoffs?
How would you extend this system to support multi-tenant memory budgets where individual components register their own limits and the system enforces them independently?
What is your strategy for testing this system, including load tests, fault injection, and validating that threshold crossings and mode transitions behave correctly under concurrency?
How do you handle concurrency and thread safety in this design, and what are the failure modes if the monitoring thread itself crashes or stalls?
How would you handle configuration persistence and rollback for threshold settings that are updated at runtime?

“This is where I spent most of the session.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

May 2026

Did a behavioral round for a software engineer role at Amazon. Just two questions, both classic leadership principle stuff.

Tell me about a challenge you faced at work.
Describe a time you disagreed with someone on your team.

“Picked a story I'd told before so at least I wasn't fumbling for an example.”

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Amazon·Software Engineer·Technical Phone Screen

May 2026

Did a technical phone screen for a Software Engineer role at Amazon. One coding question, interviewer was pretty relaxed about the whole thing.

Given an N x N matrix, rotate it 90 degrees in place.

“Classic problem but I always second-guess myself on whether to transpose first or do the reverse.”

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Amazon·Data Scientist·Technical Phone Screen

May 2026

Amazon DS interview that was basically one long system design case about elevator demand prediction. Went deeper than I expected, covering everything from problem framing to how you'd actually deploy the thing in production.

How would you frame the problem of predicting which floor the next elevator call will come from? Is it a classification problem over floors, or something like a per-floor arrival rate model?
What data and features would you use to predict elevator call origins, and which ones actually drive the prediction?
How would you construct training examples from a stream of elevator call logs without leaking future information into your features?
How would you evaluate this model offline, and what's the metric that actually matters for the business?
Your top-1 accuracy is mediocre but top-3 hit rate is strong. If there are multiple idle cars available, does that change what 'good enough' looks like and how you'd use the model output?
A new building just came online with almost no historical call data. How do you generate useful predictions on day one, and how does the model adapt as more data comes in?
Mid-day demand is nearly uniform across floors and hard to predict. How do you make the staging policy aware of its own uncertainty so it avoids making moves that could hurt more than help?

“I went straight to multiclass classification and the interviewer pushed back a bit, asking what the dispatcher actually consumes.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

May 2026

Amazon SWE interview, one round focused entirely on a deep-dive into a complex past project. The question had a lot of sub-parts and felt more like a conversation than a standard behavioral.

Walk me through the most complex project you've worked on. What drove the complexity, what design options did you consider, how did you choose between them, and what happened?

“This one sprawled.”

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Amazon·Software Engineer·Onsite - Coding / Algorithms

May 2026

Amazon SWE coding round with a string manipulation problem that looks deceptively simple but has some real gotchas once you start tracing through examples.

You have a string of single-digit box IDs. You can repeatedly pick any digit, remove it, increment it by 1 (capped at 9), and reinsert it anywhere in the string. Return the lexicographically smallest string you can produce.

“Spent the first few minutes just staring at the example trying to reverse-engineer the logic.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

May 2026

Amazon SWE interview, object-oriented design round. One big design question for the whole session, which I wasn't totally prepared for in terms of how deep they wanted to go on the billing and kitchen workflow pieces.

Design an object-oriented system for a dine-in restaurant that handles seating, ordering, kitchen state tracking, billing, bill splitting, and multiple payment methods.

“I started with tables and parties which felt safe, but then they pushed on the kitchen state machine and I kind of fumbled the transitions.”

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