← Back to Directory

Amazon interview notes, page 117 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·Technical Phone Screen

Jun 2026
Amazon Applied Scientist screen, just one ML fundamentals question from what I can tell. Pretty standard stuff but worth knowing cold.
  • What is random forest and how does it select features?

“I knew the ensemble part fine, bagging, multiple decision trees, averaging predictions.”

View Post

Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon data science interview with a hypothesis testing question that sounds straightforward until you actually have to walk through the math out loud under pressure.
  • A PM claims the average user spends $50 per month on Amazon. You think the true average is higher. You pull a sample of 100 users and get a mean of $85, with a known population standard deviation of 20. Do you reject the PM's claim?

“The numbers are almost too clean, which made me second-guess myself mid-calculation.”

View Post

Amazon·Data Scientist·Technical Phone Screen

Jun 2026
Amazon data scientist technical screen, heavy on SQL and pandas. Three big problem sets back to back, all on the same two tables. Not a vibe check at all, just pure technical depth for an hour.
  • Given a subscriptions table with known data quality issues, write SQL queries to rigorously validate four assumptions: only 'active' and 'inactive' are valid statuses, the combination of subscription_id and status_date is unique, status dates are strictly increasing per subscription, and no subscription has more than one status on the same calendar day. Return the actual violating rows for each check.
  • Using the same subscriptions table and a reference date of 2025-09-01, write SQL to return each subscription_id's latest known status and the date that status took effect.
  • In pandas, build a DataFrame with columns subscription_id, first_active_date, and last_inactive_date. First active date is the minimum status_date where status is 'active'; last inactive date is the most recent status_date where status is 'inactive' on or before 2025-09-01. Handle duplicates, unexpected statuses, and nulls when a subscription has no qualifying rows.
  • Using a pandas orders DataFrame, identify all customers who either placed fewer than 2 total orders or whose total order amount across all time is under 100.00.
  • For each calendar month derived from order_date, produce two ranked leaderboards: top 5 customers by order count and top 5 customers by total order amount. Tie-break by higher total amount first, then lower cust_id. Return all customers if fewer than 5 exist in that month.
  • Compute each customer's total spend broken down by product type and pivot the result into a wide table with columns cust_id, camera, shoes, laptop, and clothes. Fill missing product combinations with 0.00.

“This was the one that got me.”

View Post

Amazon·Software Engineer·Technical Phone Screen

Jun 2026
SQL-heavy technical screen for a BI Engineer role at Amazon. One question, but it had enough layers to keep me busy for a while.
  • Write a SQL query using a LEFT JOIN across multiple tables that includes groups with zero rows, using either a subquery in the SELECT/WHERE clause or a derived table in the FROM clause. Be prepared to explain NULL handling, performance considerations, and how you'd rewrite it using a CTE.

“The core join wasn't bad but the NULL handling follow-up tripped me up a bit.”

View Post

Amazon·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Interviewed for an ML engineer role at Amazon, basically one question about my machine learning background and that was the whole thing.
  • Walk me through your experience with machine learning.

“Pretty open-ended, which I wasn't expecting as an opener.”

View Post

Amazon·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Amazon system design screen, pretty light on details from what I remember but the scalability angle was the main focus.
  • How would your system handle 1,000 concurrent users?

“I went straight to load balancers and horizontal scaling, which felt right, but I skipped over database bottlenecks entirely until they nudged me.”

View Post

Amazon·Product Manager·Hiring Manager Screen

Jun 2026
Amazon PM interview, just one question about your first day in the role. Short but surprisingly hard to answer well on the spot.
  • What would you do on your first day as a PM?

“I rambled about meeting stakeholders and reading docs, which felt thin the moment it came out.”

View Post

Amazon·Software Engineer·Technical Phone Screen

Jun 2026
Amazon SWE interview with a graph/cycle detection problem. Pretty standard stuff for this type of role but I fumbled around a bit before landing on the right approach.
  • Given a number of courses and a list of prerequisite pairs, determine whether it's possible to complete all courses without getting stuck in a circular dependency. Return true if feasible, false otherwise.

“My first instinct was just BFS and I kind of went with it before fully thinking through why.”

View Post

Amazon·Software Engineer·Online Assessment (OA)

Jun 2026
Amazon SWE online assessment, one coding problem involving Morse code transformations. Pretty straightforward set theory problem if you know your way around hash sets.
  • Given an array of words, convert each word to its Morse code representation by concatenating the Morse code of each letter. Return the count of distinct Morse code strings produced across all words.

“Threw the words into a set after mapping each character to its Morse equivalent and concatenating.”

View Post

Amazon·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Amazon behavioral screen, pretty much what you'd expect if you've read anything about how they interview. One question, classic leadership principles angle.
  • Can you walk me through a situation where you delivered strong results despite having very little budget to work with?

“This is pure Amazon LP territory, specifically the frugality angle.”

View Post