Amazon Interview Questions — Page 1

Amazon·Software Engineer·Technical Phone Screen

Jan 2019

Amazon BI Engineer interview with a SQL window functions question focused on device-level engagement analytics. Pretty straightforward if you know your windowing syntax, but the rolling date range part trips people up.

Given a table with date, device type, and answer counts, write a SQL query that returns a rolling 7-day sum of answers for each device, ordered by date.

“The partition by device part came naturally but I fumbled the range clause for a second.”

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Amazon·Data Scientist·Technical Phone Screen

Jul 2023

Live SQL coding round at Amazon for a Data Scientist role, working through a product-sales dataset. The session mixed hands-on querying with conceptual database questions and a system design component, which I did not fully expect going in.

Write a SQL query that returns the top 10 items by total revenue within each product category, and for each category compute what percentage of total category revenue those top 10 items account for.
What is the difference between normalization and denormalization in databases, and when would you choose one over the other?
Walk through the key steps you would design into an ETL pipeline built around this sales dataset.

“This is where I lost the most time.”

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Amazon·Data Scientist·Technical Phone Screen

Sep 2023

Amazon logistics data science round, SQL heavy. Three questions that all built on the same two tables, each one adding more complexity. Felt manageable until the window function part.

Given a shipment table and a defect table, write SQL to calculate the defect rate (defects divided by shipments) for each carrier, filtered to the last 30 days.
Extend the defect rate query to show the week-over-week percentage change in defect rate per carrier using window functions.
Identify the top 3 origin-destination lanes with the highest count of 'Damaged' defects in the past quarter.

“Straightforward join and aggregate, I got through it fine.”

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Amazon·Data Scientist·Technical Phone Screen

May 2024

Amazon data scientist technical screen with a SQL-heavy question about VARCHAR primary keys and self-joins. Pretty niche topic, not your typical aggregation or window function stuff.

Given a visits table where the primary key is stored as VARCHAR but contains numeric strings, write a SQL query returning all ordered pairs of visits where v1.visit_id < v2.visit_id using lexicographic comparison. Then explain why this VARCHAR comparison can produce unexpected ordering (e.g. '9' vs '10'), and show how you'd enforce correct numeric ordering if needed.

“The self-join part came naturally enough, just FROM visits t1 JOIN visits t2 ON t1.visit_id < t2.visit_id.”

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Amazon·Software Engineer·Onsite - Multi Round

Jun 2024

Two back-to-back onsite interviews at Amazon's Santa Clara office for an SDE intern role. Applied in October, OA in March, finally got the in-person in June. Solved most of the technical problems and hit all the behavioral questions, still got rejected with zero feedback after a month of prep and a two-hour commute.

Tell me about yourself.
Describe a time you received constructive feedback. How did you respond and what did you take away from it?
Tell me about a time you had to deliver something under a tight deadline or significant pressure.
Given a list of strings, group all the anagrams together.
Find all contiguous subarrays whose elements sum to a target value k.
Walk me through a technical project you worked on. What did you struggle with, what problems did you solve, and what would you do differently?
How do you use generative AI tools in your projects? Walk me through a specific example.
Design an algorithm to determine how many cars passed through a given intersection during a specific time window, using GPS coordinates and timestamps.

“Did this twice, once per interview.”

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Amazon·Data Scientist·Technical Phone Screen

Jun 2024

Amazon data scientist interview with a SQL-heavy technical screen. Two questions, both centered on aggregate functions and window functions across retail-style schemas. Nothing too wild but you need to be comfortable writing real SQL under pressure.

Given a SALES table with columns for product_id, revenue, and quantity (which can be NULL), write SQL to compute average and standard deviation of revenue grouped by product, and add a column that replaces NULL quantity values with 0.
Using the ORDERS, ORDER_ITEMS, and CUSTOMERS tables, write SQL to join them and compute total revenue per customer, then rank customers by total revenue within each region using both RANK and DENSE_RANK.

“Pretty standard aggregation question but the NULL handling tripped me up slightly.”

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Amazon·Software Engineer·Online Assessment (OA)

Aug 2024

Took the Amazon SDE OA in August, three rounds covering DSA, an AI-assisted Spring Boot debugging section, and work simulation plus behavioral questions. Felt decent about all of it and then got rejected anyway, which stings when you can't even pinpoint what went wrong.

Given an array of integers, find the minimum total number of element replacements needed to make all values identical, where each operation replaces every occurrence of one value with another.
You are given a broken Spring Boot project. Identify the bugs and fix the code so that all provided test cases pass.

“Pretty clean problem once you see it.”

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Amazon·Software Engineer·Onsite - Coding / Algorithms

Sep 2024

Two Amazon SDE2 rounds back to back, both ending up as DSA despite R2 being listed as system design until literally the day before. The same merge problem showed up in both rounds, which was either lucky or cursed depending on how you look at it.

Merge K sorted lists. Walk through your approaches and their time/space complexity.
How many merge operations happen in a K-way merge? Explain the merge structure.
Can you solve K-way merge using a heap or priority queue? What's the optimized approach?
Behavioral questions around leadership principles, with follow-ups.

“Covered three approaches: brute linear merge at O(NK), then recursive divide and conquer, then iterative divide and conquer, both at O(N log K).”

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Amazon·Software Engineer·Onsite - Multi Round

Sep 2024

Did the Amazon SDE1 loop in Seattle through the university recruiting program, four rounds in person, and got a generic rejection with zero feedback. Coding felt fine across the board but something in the behavioral rounds clearly didn't land, and I still don't know exactly what.

Given a max request limit and a time window, design and implement a rate limiter that processes a stream of requests and decides in real time whether each one is allowed.
How would you handle concurrent access to shared rate limiter state in a distributed environment?
How do you use AI tools in your day-to-day development work?
Given a map of available inventory and a list of incoming fulfillment requests, determine for each request whether it can be fulfilled. For requests that cannot, return which items are short and by how much.
Find the top K most frequent elements in an array.
Tell me about a time you had to debug a particularly complex technical issue.
Walk me through your most significant projects, and be prepared for deep follow-up on each.

“Went with a sliding window queue approach: trim expired entries from the front, check the oldest timestamp still in the window, then allow or reject and append.”

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Amazon·Data Scientist·Technical Phone Screen

Jan 2025

Amazon Data Scientist technical screen, one meaty SQL problem that took up basically the whole session. More complex than I expected for a phone round.

Given a table of employee punch-in and punch-out events, write SQL to compute daily hours worked per employee. Your solution needs to correctly pair each 'in' event with the next 'out', split overnight shifts across calendar days, cap unmatched 'in' events at 23:59:59, ignore orphan 'out' events, round totals to the nearest 0.25 hour, and flag any days with data quality issues like overlaps or consecutive same-action events.

“This one wrecked me a little.”

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