Amazon Interview Questions

Amazon Coding & Algorithms Interview Questions

Practice 695 real Amazon interview questions for 2026. Covers all top categories — Coding & Algorithms, Behavioral & Leadership, Machine Learning, Data Manipulation (SQL/Python), and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Product Manager, and Business Intelligence Engineer roles. Real Amazon interview questions from actual interviews with detailed solutions; use this collection for interview preparation that emphasizes shipping at scale, measurable impact, and the company’s Leadership Principles. Expect coding-heavy assessments for Software Engineer candidates: frequent tree and dynamic-programming problems, two-array optimization patterns, nested object/path lookups, and system-design prompts that mirror product flows (online Minesweeper, pizza-ordering, credit-card and shipping/cost systems), plus leadership and collaboration behavioral prompts. Data Scientist rounds concentrate on experimentation and metrics (A/B design, hand p-values, D7 retention SQL), RAG/recommender evaluation, and product-impact analyses. ML Engineer questions focus on production model design, LLM/agent concepts, reliability (cold start, training stability, online vs offline gaps), and large-scale detection pipelines. PM interviews stress customer-obsessed stories, ambiguity, Alexa product launches, and domain-specific data pipelines. Prepare with timed coding practice, end-to-end experiment writeups, STAR stories framed to Leadership Principles, and mock system-design sessions.

695 Questions 1 Company08.11.2026
Showing 20 results
Role
Amazon logo
Amazon
Medium
Data Scientist

Assess Culture Fit Through Behavioral Interview Questions

Behavioral Interview: Culture Fit and Leadership You are interviewing for a Data Scientist role. The interviewer is assessing culture fit, decision-ma...

Behavioral & Leadership
21
0
65 people solved
Jul 12, 2025
Amazon logo
Amazon
Medium
Data Scientist

Optimize Predictive Analytics: Feature Engineering to Model Evaluation

End-to-End Predictive Analytics Project Walkthrough You are interviewing for a Data Scientist role. The interviewer asks you to describe a predictive ...

Machine Learning
20
0
66 people solved
Jul 12, 2025
Amazon logo
Amazon
Medium
Data Scientist

Evaluate Soft Skills Through Behavioral Interview Questions

Behavioral and Leadership Interview: Soft Skills You are interviewing for a Data Scientist role in an onsite Behavioral and Leadership round. Prepare ...

Behavioral & Leadership
113
0
319 people solved
Jul 12, 2025
Amazon logo
Amazon
Medium
Data Scientist

Choose Effective Graphs for Data Exploration

Exploratory Data Visualization: Choosing the Right Charts You are performing exploratory data analysis on a dataset with a mix of categorical and nume...

Analytics & Experimentation
12
0
50 people solved
Jul 12, 2025
Amazon logo
Amazon
Medium
Data Scientist

Compare Regularization Techniques and Their Use Cases

Compare Regularization Techniques and Their Use Cases This technical phone screen asks about model evaluation, regularization, and regression basics f...

Machine Learning
14
0
63 people solved
Jul 12, 2025
Amazon logo
Amazon
Medium
Data Scientist

Demonstrate Leadership and Ownership in Energy Analytics Role

Behavioral Interview: Ownership, Resume Walkthrough, and Energy Analytics Motivation You are interviewing for a Data Scientist role on an Amazon-style...

Behavioral & Leadership
23
0
87 people solved
Jul 12, 2025
Amazon logo
Amazon
Medium
Business Intelligence Engineer

Calculate Weekly Event Sums from Daily Counts

EVENT_LOG +------------+------+ | event_date | cnt | +------------+------+ | 2025-05-01 | 17 | | 2025-05-02 | 12 | | 2025-05-08 | 30 | +-------...

Data Manipulation (SQL/Python)
2
0
8 people solved
Jul 12, 2025
Amazon logo
Amazon
Medium
Business Intelligence Engineer

Illustrate SQL Join Results with Duplicate Keys

TABLE1 +------+ | col1 | +------+ | 1 | | 1 | | 1 | +------+ ​ TABLE2 +------+ | col1 | +------+ | 1 | | 1 | | 1 | | 1 | | 1 |...

Data Manipulation (SQL/Python)
8
0
19 people solved
Jul 12, 2025
Amazon logo
Amazon
Medium
Machine Learning Engineer

Find shortest path in a grid with obstacles

You are given a 2D grid of size m x n representing a maze. Each cell in the grid is either empty (0) or blocked (1). You are also given two coordinate...

Coding & Algorithms
5
0
66 people solved
Dec 8, 2025
Amazon logo
Amazon
Hard
Product Manager

Behavioral Deep-Dive & Leadership Scenarios

Behavioral Deep-Dive and Leadership Scenarios for Product Managers Prepare structured answers for a Product Manager phone screen or onsite covering le...

Behavioral & Leadership
15
0
149 people solved
Jul 4, 2025
Amazon logo
Amazon
Hard
Product Manager

Kindle Launch: Date vs. Scope Trade-Off

Kindle Launch Decision: Date Versus Scope Trade-Off You manage a new Kindle with eight planned features: five software features and three hardware fea...

Product / Decision Making
8
0
52 people solved
Jul 4, 2025
Amazon logo
Amazon
Hard
Product Manager

Amazon New-Service Launch Cases

Amazon New-Service Launch Cases You are asked to outline how Amazon could launch three distinct products: a restaurant table-booking app, a flower-del...

Product / Decision Making
9
0
64 people solved
Jul 4, 2025
Amazon logo
Amazon
Medium
Product Manager

Hotel Keycard System Design

Product and System Design: Replace Hotel Metal Keys With Electronic Keycards A hotel chain currently uses traditional metal keys and wants to migrate ...

Product / Decision Making
10
0
38 people solved
Jul 4, 2025
Amazon logo
Amazon
Medium
Product Manager

Launching New Amazon Services

Product Case: Launch New Amazon Services You are a Product Manager evaluating how Amazon could launch three new services: a restaurant table-booking a...

Product / Decision Making
4
0
52 people solved
Jul 4, 2025
Amazon logo
Amazon
Medium
Product Manager

Share Customer-Obsessed Leadership Stories

You are interviewing for an Amazon Logistics Product Manager role. In a first-round conversation with the hiring manager, you are asked several behavi...

Behavioral & Leadership
5
0
50 people solved
Feb 12, 2024
Amazon logo
Amazon
Medium
Machine Learning Engineer

Find two numbers that sum to target

Given an integer array nums of length n and an integer target, return the indices (i, j) (0-based) of two distinct elements such that nums[i] + nums[j...

Coding & Algorithms
2
0
28 people solved
Nov 20, 2025
Amazon logo
Amazon
Medium
Machine Learning Engineer

Implement decoder-only GPT-style transformer

Goal Implement a simplified decoder-only Transformer language model (similar in spirit to GPT) for next-token prediction. The implementation should be...

Coding & Algorithms
20
0
173 people solved
Nov 18, 2025
Amazon logo
Amazon
Medium
Data Scientist

Find daily first-order merchants with SQL

Given the table below, write a single SQL query using window functions to: A) For each calendar date (UTC), return all merchant_id(s) whose order is t...

Data Manipulation (SQL/Python)
1
1
11 people solved
Oct 13, 2025
Amazon logo
Amazon
Medium
Data Scientist

Compute join counts and window ranks

Given the following small schema and data, answer all parts precisely and justify each count/output. Tables and rows: Customers(cust_id INT PRIMARY KE...

Data Manipulation (SQL/Python)
7
0
60 people solved
Oct 13, 2025
Amazon logo
Amazon
Hard
Data Scientist

Prioritize a new warehouse proposal with data

Build vs. Lease vs. Defer: New Fulfillment Center Decision Context You are evaluating whether to open a new fulfillment center (FC) to improve deliver...

Analytics & Experimentation
3
0
70 people solved
Oct 13, 2025

Frequently Asked Questions

How difficult are Amazon interview questions for software, data, and product roles?
Amazon interviews are competitive and deliberately broad: expect medium-to-hard algorithmic coding for software roles, deep design thinking for system and architecture questions, rigorous experiment and metrics work for data roles, and leadership-driven behavioral prompts for product and PM positions. Difficulty scales with level; early-career loops focus on correctness and problem patterns, senior loops demand scalable design, tradeoff justification, and measurable impact. The Bar Raiser raises the bar on long-term ownership and cultural fit. Overall, the process weeds for both technical depth and the ability to explain tradeoffs, so prepare to demonstrate repeatable problem solving under time pressure.
What is the Amazon interview process and where do the top categories and positions appear in the loop?
Amazon typically uses a staged process: resume screen, role-specific assessments or phone screens in some tracks, then the onsite loop of 4–6 interviews including a Bar Raiser. Coding and algorithms rounds dominate for Software Engineer interviews, while system design appears in one or more senior technical rounds. Data Scientist interviews blend SQL/Python casework, A/B test design, and inferential questions. Machine Learning Engineer loops probe model deployment, offline to online debugging, and NLP/agent design. Product and BI roles focus on metrics, product tradeoffs, and Leadership Principles throughout the loop, with role-specific deep dives tied to the job description.
How long should I prepare for Amazon interviews and what should a timeline look like?
Aim for a focused 6–12 week plan for experienced roles and 4–8 weeks for early-career candidates. Weeks 1–3: shore up fundamentals — arrays, trees, graphs, DP, and core SQL windowing. Weeks 4–6: simulate timed coding rounds, practice system design high-level tradeoffs, and build STAR stories mapped to Leadership Principles. Weeks 7–10: run mock loops with behavioral pressure, refine experiment and ML case studies, and rehearse tradeoff conversations. Leave final 1–2 weeks for targeted practice on role-specific themes such as shipping costs, RAG evaluation, or Alexa product scenarios.
Which key subtopics should I master to perform well across Amazon's top roles?
Master algorithmic patterns including trees, dynamic programming, two-pointer and graph traversals, and complexity justification for coding rounds. For system design, focus on APIs, data models, scaling, caching, reliability, and monitoring. Data roles require SQL window functions, cohort and retention analysis, A/B test design and power, and RAG/evaluation methods for ML-backed features. Machine learning engineers must know model stability, cold-start strategies, online-offline mismatch debugging, and agent alignment basics. Product candidates should be fluent in metric design, customer-observed data pipelines, and prioritization with quantifiable impact.
What standout tips and common pitfalls should I know before interviewing at Amazon?
Start every behavioral or technical story with context and measurable outcomes; interviewers care about specific impact and tradeoffs. Use STAR for leadership prompts but emphasize metrics and follow-on changes. In coding, verbalize assumptions, test edge cases, and discuss complexity and alternative approaches. In design rounds, ask clarifying questions, scope deliberately, and justify scaling choices. Common pitfalls include weak quantification of impact, ignoring the Leadership Principles, failing to probe requirements, and delivering designs without operational considerations. Practice mock loops and incorporate Bar Raiser-style feedback to close gaps before the real loop.

Explore more Amazon interview questions

Jump straight to Amazon questions for a specific role or category.

By role
By category
In-depth guides
Across all companies

Featured Amazon interview prep guides

Concept walkthroughs, worked examples, and the real questions from candidate reports.

Editorial prep
Data Scientist
Amazon interview
Read the guide
Editorial prep
Software Engineer
Amazon interview
Read the guide