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Amazon interview notes, page 120 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

Jun 2026
Amazon SWE coding round with a DP problem on batching documents across GPUs to minimize padding. Pretty niche problem, not your typical LeetCode grind.
  • Given K documents with various lengths and G GPUs, partition all documents into exactly G batches (one per GPU) to minimize total padding cost, where padding cost per batch is batch_size times the max length in that batch minus the sum of actual lengths. Output the minimum total padding cost and one valid batching.

“The key insight I kept second-guessing myself on was whether sorting first was actually valid.”

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Amazon·Data Scientist·Technical Phone Screen

Jun 2026
Amazon Data Scientist interview with a heavy pandas/SQL flavor. The whole session was basically one big scenario around e-commerce order data, and they wanted working code, not just pseudocode.
  • Given an orders table, write Python (pandas) code to return all customer IDs who have placed fewer than 2 orders OR whose total spend is under 100.
  • For each calendar month, find the top 5 customers by (a) total number of orders and (b) total order cost. Write Python code to produce both rankings.
  • Produce a wide-format DataFrame with columns for cust_id and each product type (camera, shoes, laptop, clothes), where each cell shows total spend by that customer on that product.

“Straightforward groupby, but the OR condition is where people trip up.”

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Amazon·Software Engineer·Onsite - Multi Round

Jun 2026
Went through day one of the Amazon Data Engineer loop and it was all technical. Got some feedback at the end that felt positive but one comment from the interviewer has been living rent-free in my head since.
  • How did you approach balancing business context versus technical depth when discussing your past projects?

“The interviewer told me I should've led with more business framing before jumping into the technical side of my projects.”

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Amazon·Frontend Engineer·Technical Phone Screen

Jun 2026
Amazon frontend interview with a coding round that leaned more algorithmic than I expected. The question was about log parsing, which sounds simple enough, but they pushed pretty hard on the optimal solution.
  • You're given an array of logs, each with a status (success or failure) and a timestamp. Failures are monotonic, meaning once a failure appears, everything after it is also a failure. Find the timestamp of the first failure, or return that no failure exists. Walk through both a linear scan and a binary search solution.

“I went straight to the linear scan from the end, which works fine but is O(n) and I kind of knew they'd push back.”

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Amazon·Product Manager·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Amazon for a PM role, pretty much one question that took up most of the conversation.
  • Tell me about a time you disagreed with a manager or peer over something that actually mattered to the business.

“This is the kind of question where you think you have a good story until you're halfway through telling it and realize it sounds like you just complained and then gave up.”

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Amazon·Software Engineer·Onsite - Multi Round

Jun 2026
Interviewed for an Amazon SDE intern role and it was a rough one. Two coding rounds back to back, couldn't fully implement the first problem and needed a lot of hand-holding on the second. Behavioral stuff went okay but I'm genuinely not sure if that's enough to save it.
  • Solve a coding problem from scratch, implementing a working solution.
  • Implement a graph-based problem, then solve a follow-up variation of it.
  • Leadership principle behavioral questions.

“Couldn't get the implementation out.”

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Amazon·Software Engineer·Online Assessment (OA)

Jun 2026
Took the Amazon OA recently, two questions total: one DSA and one AI backend. Got through the DSA fine but the backend question was rough, only 1 out of 6 test cases passed, so now I'm just waiting and hoping for the best.
  • A data structures and algorithms problem included in the Amazon online assessment.
  • An AI backend implementation question included in the Amazon online assessment.

“This one went okay.”

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Amazon·Software Engineer·Online Assessment (OA)

Jun 2026
Amazon OA for a SWE role, one algorithmic problem about minimizing days to finish reading chapters under some sliding window constraints. Pretty niche problem type, felt like a binary search on answer situation but took me a while to see it.
  • Given an array of chapter page counts, a window size k (consecutive chapters per day), and a daily page limit p per chapter, find the minimum number of days to reduce all chapters to zero pages.

“Took me embarrassingly long to realize this screams binary search on the answer.”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE interview with a graph theory problem that looked straightforward on paper but had more depth than I expected once they started asking about tradeoffs between approaches.
  • Given a directed graph as an adjacency list with n vertices and m edges, detect whether the graph contains a cycle. Implement a solution, explain its time and space complexity, and walk through both a DFS-with-recursion-stack approach and a topological sort approach using Kahn's algorithm.

“I started with DFS because that felt natural, tracking nodes in three states: unvisited, currently in the recursion stack, and fully processed.”

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Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE interview with a pretty gnarly algorithmic problem involving game theory, dynamic programming, and resource constraints. Not your typical LeetCode grind, this one required actual thinking about state space design under pressure.
  • You and a coworker take turns unloading warehouses in sequence. On your turn you remove exactly m items from the current warehouse; on the coworker's turn they remove exactly n items. If your removal empties a warehouse you score a point. You have up to k skip tokens total, each of which forces the coworker to forfeit their next turn so you go again immediately. Skips can be concentrated on one warehouse or spread across all of them. Design an algorithm to maximize your total score, and analyze its time and space complexity.

“This wrecked me a little.”

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