Candidate reports describe practical SQL, project and behavioral discussions, occasional business cases, and later interview formats that vary by team.
$129K
Avg. Base Comp
$185K
Avg. Total Comp
2-7 rounds
Typical Rounds
2-3 months
Process Length
Amazon Data Analyst candidates report a mix of practical SQL and discussion of prior analytical work. Be ready to explain your reasoning as you work. Recent accounts included live questions on GROUP BY, SUM, denormalizing tables, and edge cases. Candidates also described data-cleaning fundamentals, data extraction, basic Power BI questions, and—in one broader process—Python and statistics.
Business judgment may be tested alongside technical work. Some candidates encountered a short business case or were asked to walk through a detailed analysis they had used to solve a problem. Practice stating assumptions, selecting an approach, and turning findings into a clear recommendation. Because formats differed across the reports, use the recruiter’s outline to decide how much time to devote to cases versus technical exercises.
Behavioral preparation matters throughout the reported process. Candidates discussed projects they were proud of, challenges during projects, motivation for Amazon and analytics, and examples connected to Leadership Principles, including Deep Dive. Prepare concise stories that identify the problem, your personal contribution, the analysis or action you took, and the outcome. Be ready to answer follow-up questions about the details rather than stopping at a high-level summary.
Reported structures ranged from a shorter screen-and-interview path to a six-round process with assessments, onsite-style interviews, and a bar raiser. The evidence does not establish a reliable overall timeline. Confirm the sequence with your recruiter, then prioritize live SQL practice, clear project explanations, and behavioral stories relevant to the team’s stated format.
Synthesized from 20 candidate reports by our editorial team.
Had an interview recently?
Share your experience. Unlock the full guide.
Real interview reports from people who went through the Amazon process.
Share your own interview experience to unlock all reports, or subscribe for full access.
Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Amazon
Write a query that returns all neighborhoods that have 0 users.
| Question | |
|---|---|
| 2nd Highest Salary | |
| Rolling Bank Transactions | |
| Customer Orders | |
| Comments Histogram | |
| Closest SAT Scores | |
| Top Three Salaries | |
| Monthly Customer Report | |
| Compute Deviation | |
| Experiment Validity | |
| Download Facts | |
| Random SQL Sample | |
| Subscription Overlap | |
| Month Over Month | |
| Button AB Test | |
| Prime to N | |
| Upsell Transactions | |
| Paired Products | |
| Top 3 Users | |
| Swipe Precision | |
| Longest Streak Users | |
| Bank Fraud Model | |
| Encoding Categorical Features | |
| Identifying User Sessions | |
| Rolling Average Steps | |
| Exam Scores | |
| Weekly Aggregation | |
| Network Experiment Design | |
| Bagging vs Boosting | |
| Average Quantity |
Synthesized from candidate reports. Individual experiences may vary.
Candidates reported online or SQL assessments before live interviews, while others described an initial screen combining background discussion with technical questions. Prepare a concise introduction to your experience and be ready to move into practical analytical reasoning.
Several reports describe live SQL rather than only theoretical questions. Examples included GROUP BY and SUM, joins, table denormalization, transaction-style problems, and edge cases. Explain your approach aloud, clarify assumptions, and use test cases where helpful.
Some candidates encountered a short business case, including a market-sizing-style prompt, or discussed a detailed analysis they had used to solve a problem. Practice structuring an ambiguous question, stating assumptions, and communicating a recommendation in business terms.
Candidates frequently reported questions about projects, work experience, motivation, difficult situations, and Amazon leadership principles. Recent accounts specifically mention Deep Dive, project challenges, and why Amazon or data analytics. Use concrete examples with a clear personal contribution and result.
Reported later stages range from a hiring-manager conversation to multi-session virtual loops. Some accounts included manager, analytical problem-solving, SQL, PM, or bar-raiser conversations, while others described shorter paths. Use recruiter-provided themes to prioritize your preparation.
