Amazon Data Analyst Interview Process — 2026 Guide
Based on real candidate experiences and interview reports shared on Glassdoor, LinkedIn, and community forums. Amazon hires data analysts across 4 analytics roles in India. Here is exactly what to expect — round by round — and how to prepare.
Amazon Data Analyst Interview Rounds
Round 1: Resume Screening
What they look for
Relevant SQL and analytics experience, portfolio projects, and clean formatting. Skills > degree for most ${company.name} analytics roles. 1-page resume, quantified achievements, 3+ relevant projects.
Round 2: Online Assessment
What is tested
SQL queries (beginner to intermediate), logical reasoning, and sometimes a short data interpretation problem. Duration: 45–90 minutes. HackerRank, Cocubes, or internal platforms are common.
Round 3: Technical Interview
Deep dive into
Advanced SQL (window functions, CTEs, query optimization), statistics (distributions, hypothesis testing, A/B testing basics), and a mini case study. Cohort analysis and funnel analytics are common.
Round 4: Managerial / HR Round
Focus areas
Behavioural questions (tell me about a time you found an insight that changed a decision), compensation discussion, culture fit assessment, and clarification of career goals. Prepare STAR-format answers for 5–6 typical scenarios.
What Amazon Actually Looks For
Beyond the job description — what consistently differentiates selected candidates:
Data-driven decisions
Amazon famously runs on metrics. Every product decision, pricing change, and customer experience improvement is backed by data. They expect analysts to think in experiments and measure everything.
Ownership mentality
Candidates who show they have dug deep into problems — not just reported numbers — stand out. They want analysts who ask "why" not just "what".
SQL at speed
Expect to write complex SQL on the spot. Window functions, CTEs, and query optimization are not optional. Practice writing from scratch, not just reading.
Most Common SQL Questions at Amazon
Real-style questions from E-commerce/Cloud analytics interviews. Practice writing the SQL — not just reading the answers:
Q1: Find the top 5 products by revenue in the last 30 days, but only include products that were sold on at least 10 different days.
Hint: Use GROUP BY with HAVING, and filter by date range. Think about how to count distinct days per product.
Q2: Calculate the 7-day rolling average of daily orders for each city.
Hint: Window function: AVG(orders) OVER (PARTITION BY city ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW)
Q3: Find customers who placed orders in January but not in February.
Hint: Classic "NOT IN subquery" or LEFT JOIN + IS NULL pattern. This tests basic set logic.
Q4: Write a query to find the cohort retention rate: what % of users who first ordered in a given month came back in the following month?
Hint: This requires a self-join or CTE to find each user's first_order_month, then count returns. Tests advanced analytical thinking.
Q5: Identify products where the return rate is higher than 20% and flag them.
Hint: JOIN orders with returns table, calculate return_count / order_count per product, filter on HAVING.
Technical Skills Amazon Tests
How to Prepare in 2 Weeks
Structured day-by-day plan for the Amazon interview:
Days 1–2
- •SQL basics: SELECT, WHERE, GROUP BY, ORDER BY, HAVING
- •Practice 10 basic SQL problems on LeetCode or HackerRank
Days 3–4
- •SQL intermediate: JOINs (inner, left, right, full), subqueries
- •Practice join-heavy problems on real-world datasets
Days 5–7
- •SQL advanced: Window functions (ROW_NUMBER, RANK, LAG, LEAD), CTEs
- •Statistics basics: mean, median, standard deviation, distributions
Days 8–9
- •Study cohort analysis, funnel analysis, and retention curves
- •Build one cohort analysis on a public dataset (Amazon reviews, etc.)
Days 10–11
- •Review e-commerce metrics: CVR, AOV, LTV, NPS, return rate
- •Research company-specific challenges and recent initiatives
Days 12–14
- •Mock interview: 2 SQL problems + 1 case study
- •Prepare storytelling narrative for each portfolio project
Red Flags That Get Candidates Rejected
✗ Memorising answers without understanding
Interviewers ask follow-up questions to test depth. If you cannot explain why your SQL works, it shows immediately.
✗ Jumping to conclusions from data
Saying "the data shows X causes Y" without checking for confounds or data quality issues raises red flags for analytical rigor.
✗ No opinion on your own projects
Candidates who cannot say "if I redid this project, I would do X differently" appear to have not actually done the work themselves.
✗ Ignoring the business context
Giving technically correct but practically useless answers. Interviewers want analysts who ask "what decision does this need to support?"
5 Smart Questions to Ask in the Interview
These demonstrate analytical curiosity and seriousness — which is exactly what Amazon looks for:
- 1.How does the analytics team's work influence product or business decisions at Amazon?
- 2.What does the data infrastructure look like — what tools does the team use day-to-day?
- 3.What is the biggest analytical question you are trying to answer right now, and what makes it hard?
- 4.How does a new analyst typically ramp up — what does the first 3 months look like?
- 5.What separates a good analyst from a great one at this team specifically?
Interview Guides by Role at Amazon
Data Analyst
Data Analysts collect, process, and analyze structured data to generate act…
₹4-6 LPA – ₹15-25 LPA →
Data Scientist
Data Scientists build predictive models, perform statistical analysis, and …
₹6-10 LPA – ₹20-40 LPA →
Machine Learning Engineer
ML Engineers build, deploy, and maintain machine learning models in product…
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Product Analyst
Product Analysts track product metrics, conduct user behavior analysis, and…
₹4-7 LPA – ₹16-28 LPA →
All Data Roles — Amazon Interview
Frequently Asked Questions
How many rounds does Amazon have for data analyst interviews?+
Amazon typically has 4 rounds: resume screening, online assessment, technical interview (SQL + case study), and HR/managerial round. Some roles add a take-home assignment between rounds 2 and 3.
What is the Amazon data analyst salary range?+
Amazon pays ₹15-28 LPA for data analytics roles. The lower end of this range is for fresher/entry-level roles, and the higher end for senior analytics roles with 4+ years of experience and specialised domain skills.
How difficult is the Amazon data analyst interview?+
Difficulty is moderate to high. SQL is consistently hard across all rounds. Deep technical questions test whether you can write SQL under pressure.
Does Amazon do a take-home assignment?+
Some Amazon analytics roles include a take-home data challenge — typically a business scenario with a dataset where you write SQL, do EDA in Python, and present findings. If you get one, the quality of your presentation and the insight quality matter as much as technical execution.
Want to crack the Amazon interview? Start with the right foundation.
The SQL depth, statistics knowledge, and case study thinking that Amazon tests — these are not things you can cram in a week. The SkillsetMaster course builds them systematically over 3–6 months, with real projects, live mentors, and a structured curriculum that matches what top analytics teams actually test.