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Amazon interview notes, page 80 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·Product Manager·Onsite - System Design / Architecture

May 2026
Amazon PM interview with a single system design question that was way more hardware-heavy than I expected. Not a typical product sense round at all.
  • Design the architecture for a hardware device that measures temperature and social distancing among warehouse employees during a pandemic.

“I went straight to the software layer and kind of glossed over the actual hardware constraints, which I think hurt me.”

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Amazon·Software Engineer·Onsite - Coding / Algorithms

May 2026
Amazon SWE coding round, one problem the whole session. The constraint about guards only moving left or staying put made it trickier than a typical greedy problem, and I spent way too long second-guessing whether DP was even necessary.
  • You have n cities with a population array and a binary string indicating which cities start with a guard. Each guard can either stay or move one position to the left, no two guards can share a city. Maximize the total population of protected cities.

“The movement constraint is what gets you.”

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Amazon·Data Scientist·Technical Phone Screen

May 2026
Amazon data scientist interview with a practical EDA scenario. The question was open-ended enough that I kept second-guessing whether I was going too deep into the technical weeds or not deep enough for the business angle.
  • You're handed an unfamiliar dataset and need to quickly surface insights for business stakeholders. Walk through how you'd profile the data, assess its quality, and decide which visualizations to build.

“I started with the profiling angle which felt right, row counts, column types, null rates, that kind of thing.”

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Amazon·Software Engineer·Onsite - Product Sense / Strategy

May 2026
Amazon business analyst interview, one round focused on strategy. The question was straightforward on the surface but the follow-up directions it could go made it a bit of a maze.
  • You're launching a new feature. How would you measure its strategic impact on growth?

“I went straight to metrics and kind of skipped the part where you define what 'growth' even means for the feature in question.”

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Amazon·Software Engineer·Technical Phone Screen

May 2026
SQL-heavy technical screen for a software engineering role at Amazon. Just one question but it had multiple layers and they kept pushing to see how far I'd take it.
  • You have a products table with a department/category/subcategory hierarchy and a click_log table with user and event data. Write a query to count distinct users who clicked products in a given department within a time range. Then extend it to return counts for all departments at once.

“Started with the filtered version which was fine, just a join plus COUNT(DISTINCT user_id) with a WHERE on department and event_time.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

May 2026
Amazon solutions architect interview, one big open-ended question about modernizing a bank's legacy systems. Not a lot of context given upfront, which made it harder than expected.
  • How would you digitalize a bank that is running on legacy data and infrastructure?

“This question has a lot of surface area and I kind of froze for a second trying to figure out where to even start.”

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Amazon·Software Engineer·Technical Phone Screen

May 2026
Amazon data science interview with a focus on ML fundamentals. The linear regression question felt routine but I probably undersold my answer by not going deep enough on the diagnostics side.
  • What are common problems or failure modes you encounter with linear regression?

“I rattled off multicollinearity and heteroscedasticity and then kind of stalled.”

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Amazon·Software Engineer·Online Assessment (OA)

May 2026
Took the SDE2 online assessment for Amazon and had a mixed bag: the DSA portion went well but the Spring Boot authentication section was rough, and now I'm sitting here wondering if partial credit means anything.
  • Solve a hard or medium-hard dynamic programming problem involving string manipulation.
  • Implement authentication functionality in a Spring Boot application.

“Got full marks here which felt good, but I'd be lying if I said I wasn't surprised.”

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Amazon·Software Engineer·Technical Phone Screen

May 2026
Amazon SWE coding round, basically just the classic LRU cache problem. Nothing fancy, but it's the kind of question that punishes you if you haven't actually implemented it from scratch before.
  • Implement an LRU Cache supporting get and put operations, both in O(1) time complexity.

“You'd think this is easy until you're staring at a blank editor.”

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Amazon·Software Engineer·Onsite - System Design / Architecture

May 2026
Pretty intense system design round at Amazon focused almost entirely on Aurora internals and database engine theory. If you're not comfortable going deep on storage architecture, replication, and concurrency control, this one will hurt.
  • How does Aurora's storage architecture differ from a traditional MySQL or Postgres deployment, and what are the implications of separating compute from storage?
  • Walk me through how Aurora handles replication across availability zones, including how the quorum model works and why that design was chosen.
  • Explain the role of the write-ahead log in crash recovery, and describe how Aurora's approach differs from the traditional checkpoint-and-redo flow.
  • How does MVCC work, and why does it allow readers to not block writers?
  • How does a database engine handle lock conflicts under high write concurrency, including row-level locks, gap locks, and deadlock detection?
  • What are the core trade-offs between consistency, latency, and throughput in a cloud-native database, and how do you reason about them when designing a system?

“This was the opener and I thought I had it, but I kept framing it like a normal replication setup and the interviewer kept pushing.”

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