Amazon Business Intelligence interviews reported by candidates combine SQL assessments, technical screens, and a loop built around Leadership Principles, with a Bar Raiser round in several accounts.
$130K
Avg. Base Comp
$163K
Avg. Total Comp
3-5 rounds
Typical Rounds
Not reported
Process Length
Candidates describe the Amazon Business Intelligence interview as SQL first, Leadership Principles throughout. Several start with a recruiter or HR screen and an online assessment, which one candidate described as SQL, multiple-choice and working-style questions. A technical phone screen follows, and most accounts end with a virtual loop. One candidate who received an offer reported a HackerRank step and a one-hour technical screen. A loop of one-hour rounds followed, with a Bar Raiser, a hiring manager, a customer PM, a senior BIE, a senior data engineer and a senior data scientist.
The SQL reported is practical rather than algorithmic. Candidates mention joins (including NULL behavior), window functions such as LAG, ROW_NUMBER and rolling averages, CTEs, top-N queries, and the classic second-highest-salary problem. Some assessments were harder than expected, with output-prediction questions and scenario-style multiple choice on query performance. Dashboard prompts also appear, such as explaining how you would investigate a drop in a business metric or define a North Star metric and guardrails. Ask clarifying questions and state assumptions before you write anything.
Behavioral depth matters as much as the technical work. Candidates report that Leadership Principles questions came up in most rounds, with heavy follow-ups on your specific contribution. A few mention A/B testing or statistics, Python, ETL and data modeling, so check the job description for the level you target. Experiences vary widely, including one report of a loop that pushed beyond typical BI scope.
Synthesized from 50 candidate reports by our editorial team.
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| Question | |
|---|---|
| Rolling Bank Transactions | |
| Customer Orders | |
| Comments Histogram | |
| Closest SAT Scores | |
| Empty Neighborhoods | |
| Subscription Overlap | |
| Top Three Salaries | |
| Monthly Customer Report | |
| Experiment Validity | |
| Average Quantity | |
| Manager Team Sizes | |
| Month Over Month | |
| Button AB Test | |
| Flight Records | |
| Upsell Transactions | |
| Top 3 Users | |
| Longest Streak Users | |
| Merge Sorted Lists | |
| Compute Deviation | |
| Project Pairs | |
| Retailer Data Warehouse | |
| Rolling Average Steps | |
| Address Schema | |
| Download Facts | |
| Total Time in Flight | |
| Daily Retention Summary | |
| Monthly Product Sales | |
| Group Success | |
| Size of Joins |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report starting with a recruiter or HR call covering background and logistics. Some mention a short questionnaire, such as one on visa status, and one candidate said it took about three weeks to reschedule the interview. This stage typically involves little technical depth.
Several candidates describe an online assessment, often on Hackerrank or a similar platform. Reported content includes SQL problems, multiple-choice SQL questions and working-style or Leadership Principles questions. One candidate called the SQL easy but the multiple-choice items convoluted, while others reported harder SQL. Formats appear to vary by candidate.
Candidates report a 30 to 75 minute technical screen mixing live SQL with questions about past projects and at least one Leadership Principles question. Topics include joins, CTEs, window functions and second-highest-salary problems. Some describe whiteboard or notepad-style coding without compilation, so syntax accuracy may matter.
Candidates report loops of about three to five one-hour rounds. One offer report listed Bar Raiser, hiring manager, customer PM, senior BIE, senior data engineer and senior data scientist conversations. Content reportedly mixed SQL, optimization, dashboards, A/B testing, ETL or data modeling, and Leadership Principles, depending on the interviewer.
Candidates describe a Bar Raiser round focused on Leadership Principles and project deep dives, with repeated follow-ups on your own contribution, ambiguity and results. Reported advice is to prepare several quantified STAR stories using I rather than we. Outcomes among reports are mixed, with offers and rejections both mentioned.
