Four candidates describe Flipkart Business Analyst interviews that mix SQL, probability puzzles, guesstimates, e-commerce cases and resume deep-dives. Formats varied, and two candidates reported no final answer.
$21K
Avg. Base Comp
$25K
Avg. Total Comp
3-6 rounds
Typical Rounds
4 weeks
Process Length
Flipkart Business Analyst interviews, as four candidates describe them, put analytical reasoning ahead of any single tool. SQL is the most consistent thread: one candidate faced an aptitude test covering SQL, logical reasoning and statistics, another had five or six joins, group by and having questions, and a third was asked for CTE queries on customers inactive for 30 days, AOV and ASP.
The second pattern is puzzles and estimation. Candidates recall probability questions (marbles in bags, repeated digits in a five-digit number), a lap-speed problem, a water jug problem and an estimate of annual iPhone sales in India. One candidate also got a business case on declining Netflix viewership in India. Another was asked how to pick 1,000 pin codes out of 17,000 to compare delivery metrics with a competitor, plus how to reduce return-order scams.
Third, expect questions on your own work. One candidate was pressed on the methodology and assumptions of a machine learning project, and also faced basic array and string coding problems. Another was asked why they were moving from a tech background into business analysis.
Formats differed a lot. One candidate described three main rounds over about four weeks. Another described an HR screen followed by five back-to-back interviews of 35-40 minutes on business acumen and situational questions. Two candidates reported never getting a final decision, and the other two reported rejections, so plan your follow-up accordingly.
Practice talking through your reasoning aloud. Several candidates said interviewers cared about how they structured an ambiguous problem, not only the final number.
Synthesized from 4 candidate reports by our editorial team.
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Real interview reports from people who went through the Flipkart process.
The interview process at Flipkart for the Business Analyst role had multiple layers, and it became clear early on that they were looking for someone who could bridge technical and business thinking. I started with an initial HR screening, which was fairly standard—they wanted to understand my background and motivation for joining. What surprised me was how much the technical rounds varied depending on who was conducting them.
In the first technical round, the interviewer focused heavily on a machine learning project I'd worked on previously. He asked some genuinely tough questions about the methodology, assumptions, and trade-offs I'd made. It wasn't just surface-level—he wanted to understand my thought process and how I'd approached the problem. This round lasted about 15 to 20 minutes and felt more like a technical deep-dive than a typical screening. After that, there was a coding round where they hit me with basic LeetCode-style problems around arrays and strings. Nothing too complex algorithmically, but it tested whether I could write clean, functional code under time pressure.
The later rounds shifted toward business skills. I faced SQL questions that were quite practical—things like identifying customers who hadn't purchased in the last 30 days, calculating key ecommerce metrics like AOV (average order value) and ASP (average selling price), and writing queries with CTEs. They also threw in a case study that required me to think about stakeholder management and how I'd approach a real business problem. An interviewer asked why I wanted to transition into this role from a tech background, and I realized they were genuinely concerned about fit and motivation, not just technical chops. There were also some HR-style questions mixed in toward the end, along with discussions about working in cross-functional environments.
Overall, the process tested a blend of technical skills—SQL and basic Python—alongside business acumen and communication. If you're going in, expect to defend any project you put on your resume and be ready to discuss real business metrics and how data drives decisions at a company like Flipkart.
Prep tip from this candidate
Prepare for deep technical questions on any project you highlight in your resume—interviewers will probe your methodology and assumptions. Additionally, drill SQL queries on practical ecommerce metrics like customer retention, AOV, and cohort analysis, as these came up repeatedly. Be ready to articulate why you're transitioning from a tech background into business analysis and how that combination is a strength.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Flipkart
How would you assess if a coin is fair after observing 8 tails in 10 flips?
| Question | |
|---|---|
| Jars and Coins | |
| Bagging vs Boosting | |
| Same Side Probability | |
| HHT or HTT | |
| Max Quantity | |
| Flipping 576 Times | |
| Underpricing Algorithm | |
| Hurdles In Data Projects | |
| Biased Random Number Generator | |
| Biased five out of six | |
| Possibly Biased Coin | |
| All Tails Consecutive | |
| Count Transactions | |
| Walking Robot | |
| Seller Type Modeling | |
| Merchant Dashboard Design | |
| Why Do You Want to Work With Us | |
| Evaluating Revenue Decline | |
| Bag of Different Coins | |
| Meta in an Emerging Market | |
| 2nd Highest Salary | |
| Empty Neighborhoods | |
| Customer Orders | |
| Longest Streak Users | |
| Top 3 Users | |
| Scrambled Tickets | |
| Button AB Test | |
| Rolling Bank Transactions | |
| Paired Products |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial HR or recruiter call covering their background, current role and motivation for joining. One candidate who came from a tech background was asked why they wanted to move into business analysis, so prepare a clear answer to that.
Candidates report SQL-focused rounds, in one case preceded by an aptitude test covering SQL, logical reasoning and statistics. Questions typically involved joins, group by, having, CTEs and practical e-commerce metrics such as AOV, ASP and inactive customers. Another candidate went straight to live discussion instead of an online test.
Candidates describe puzzle and case-style questions: probability with marbles or digits, a water jug problem, an iPhone sales estimate for India, a Netflix viewership diagnosis, pin-code sampling and return-fraud prevention. One round reportedly ran about an hour and felt conversational, with emphasis on how you reason through edge cases.
One candidate was probed on a machine learning project and given basic array and string coding problems. Another reported five back-to-back 35-40 minute interviews on business acumen and cross-functional scenarios, ending with an HRBP conversation. Outcomes varied: two rejections and two cases with no final decision reported.
