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Amazon interview notes, page 116 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·Online Assessment (OA)

Jun 2026
Amazon OA for a SWE role. One coding problem, greedy/sorting type, not too bad once you see the pattern but easy to overthink.
  • Given two arrays of equal length, one representing sizes and one representing costs, make all elements in the size array distinct by only incrementing values. Each increment adds the corresponding cost. Find the minimum total cost to achieve this.

“Took me a minute to realize you always want to increment the cheaper element when there's a collision, not just the one that came later.”

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Amazon·Product Manager·Onsite - Behavioral / Leadership

Jun 2026
Amazon PM interview, one behavioral question about risk-taking under time pressure. Pretty standard loop format but this particular question tripped me up more than I expected.
  • Tell me about a time you took a calculated risk when speed was critical.

“I had a story ready but the 'calculated' part is what got me.”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon coding round, one problem the whole time. You get logs, you find sequences, you figure out which ones repeat the most. Seems straightforward until you're actually in it.
  • Given a collection of logs, identify recurring sequences and return the sequences that appear most frequently.

“My first instinct was to just throw a hashmap at it, which was the right direction, but I fumbled around with how to define a 'sequence' before settling on something.”

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Amazon·Data Scientist·Technical Phone Screen

Jun 2026
Amazon data scientist interview focused on ML system design for NLP under latency constraints. The technical depth expected was no joke, mixing architecture tradeoffs with ensemble theory in the same breath.
  • Compare RNNs and Transformers across architecture design, parallelism during training, how they handle long-range context, and their training dynamics.
  • Explain bagging and boosting as ensemble methods and describe the conditions under which you'd choose one over the other.

“I knew this cold but still fumbled the parallelism angle a bit.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Interviewed for a solutions architect role at Amazon, got asked about scalability. Pretty thin on details but it felt like a system design screen.
  • How would you explain the concept of scalability?

“Felt like a warmup but I still fumbled it a bit.”

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Amazon·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at Amazon with a product strategy question about the video service business. Pretty sparse on details but the core question was a classic keep-or-cut framing.
  • For Amazon's video streaming service, would you recommend continuing to offer it or shutting it down? Walk through your reasoning.

“This is the kind of question where you can spiral fast if you don't anchor on a framework early.”

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Amazon·Data Scientist·Technical Phone Screen

Jun 2026
Amazon Data Scientist interview with a subscription analytics problem that mixed SQL and pandas in a single question. The setup was deceptively simple but they clearly wanted to see how you think about data quality before jumping to the actual aggregation.
  • Given a subscriptions table with subscription_id, status, and status_date columns, write a SQL query to investigate the structure of the data (e.g., check uniqueness of id+date combinations, validate which status transitions are actually present). Then in pandas, build a DataFrame that shows for each subscription_id the first date it was ACTIVE and the last date it was INACTIVE.

“The SQL part tripped me up more than I expected.”

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Amazon·Software Engineer·Online Assessment (OA)

Jun 2026
Amazon SWE coding round with a query tree problem I hadn't seen before. Not your typical LeetCode grind, this one felt more like a compiler/DB internals question which threw me a bit.
  • Implement a constant folding algorithm for a query tree. The tree has three parts: a projection list, a predicate list, and a nested subquery list. You need to traverse the tree, fold safe nodes, and recursively convert queries into subqueries, then return the simplified tree.

“Took me a minute to even parse what 'constant folding' meant in this context.”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE coding round, one algorithmic problem about graph traversal. Pretty focused session, no fluff.
  • Given a course catalog represented as an adjacency list, write a function that checks whether the catalog contains any cyclic dependencies between courses.

“Cycle detection in a directed graph.”

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Amazon·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Amazon for a SWE role. Just the one question but it took me longer than expected to land on a good story.
  • Tell me about a time you had an unpopular idea.

“I blanked for a second.”

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