Chewy Data Analyst interview typically runs 4 rounds: recruiter screen, hiring manager, technical round, and loop interviews. Timeline is about one day for the loop, and the process is notably principle-driven with some SQL and BI screening.
$131K
Avg. Base Comp
$157K
Avg. Total Comp
4
Typical Rounds
3-5 weeks
Process Length
We’ve seen Chewy evaluate data candidates as operators, not just query writers. A recurring theme in our candidate reports is that interviewers want to know whether you can turn messy business questions into something actionable for merchandising, operations, or customer-facing teams. That shows up in the way they probe stakeholder conflict, project tradeoffs, and how you explain technical choices to non-technical partners. Candidates who only frame their experience as analysis tend to feel underpowered; the stronger responses connect the work to a business decision and show ownership of the outcome.
Another pattern we’ve noticed is that Chewy does not separate “behavioral” and “technical” as cleanly as many companies do. Multiple candidates reported SQL surfacing in conversations that were supposed to be about background or leadership, which tells us the team is listening for analytical fluency in every interaction. The technical bar also seems practical rather than academic: exact SQL matters, especially around window functions, optimization, and query correctness without much room to test. That means the interview rewards people who can reason cleanly under pressure and explain why a query is structured a certain way, not just those who memorize syntax.
The other non-obvious signal is cultural fit through Chewy’s principles. Our candidates report that interviewers expect those values to come through naturally in STAR stories, not as a scripted recitation at the end. The strongest candidates weave those principles into examples of collaboration, ambiguity, and decision-making from the start. In practice, Chewy seems to favor analysts who are commercially minded, technically precise, and comfortable operating in a highly cross-functional environment where the best answer is the one that can survive both scrutiny and execution.
Synthesized from 1 candidate report by our editorial team.
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Real interview reports from people who went through the Chewy process.
I interviewed for a Senior Data Analyst / Business Intelligence Engineer role at Chewy. The process consisted of multiple stages:
Recruiter Screen: A high-level discussion about my background and role expectations.
Hiring Manager Round (45 min–1 hr): We discussed our respective backgrounds, role expectations, the stakeholder landscape, and situational/behavioral questions. I was asked things like 'How do you manage stakeholder conflicts?', 'How do you use technical tools to solve a business problem?', and I did a deep dive into a past project. Unexpectedly, some technical SQL questions also came up in this round.
Technical Round: This was conducted with a technical director. It covered 8–10 SQL questions ranging from easy to hard, including optimization and window functions. Some questions only required pseudocode or high-level responses, while one or two required actual coding on a platform with test cases. There were also Power BI technical questions covering field parameters, dimensions, and measures. Notably, for most SQL questions there was no interactive coding environment — I had to write exact, correct queries without the ability to test or experiment.
Loop Round (4 interviews in one day, ~45 min each): Three behavioral rounds and one technical round. Each behavioral round covered two of Chewy's company principles, and I was expected to demonstrate alignment through STAR-method stories from my work experience. I prepared by weaving Chewy's principles into all of my answers from the very first interview round.
I was awaiting a final response and offer at the time of writing. I felt well-prepared overall, and I attribute a lot of that to Interview Query's structured, company-specific question sets, which made my prep much more efficient.
Prep tip from this candidate
For Chewy's BI/Analytics interviews, prepare 3–4 STAR stories that explicitly map to their company principles (have these ready before your first call), and practice writing SQL queries without an IDE—focus on window functions, optimization, and exact syntax since you won't have a testing environment.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Chewy
Select the 2nd highest salary in the engineering department
| Question | |
|---|---|
| Customer Orders | |
| Random SQL Sample | |
| Top 3 Users | |
| Booking Regression | |
| Max Quantity | |
| Random Forest Explanation | |
| Marketing Channel Metrics | |
| Retailer Data Warehouse | |
| Valid Anagram | |
| Monthly Product Sales | |
| Hurdles In Data Projects | |
| Banner Ad Strategy Success | |
| Digital Marketing Metrics | |
| String Palindromes | |
| Client Solution Pushback | |
| Weighted Average Sales | |
| Why Do You Want to Work With Us | |
| Generative AI Privacy | |
| Marketing Dollar Efficiency | |
| Identical Pen Pricing | |
| Direct Mail | |
| Empty Neighborhoods | |
| Rolling Bank Transactions | |
| Monthly Customer Report | |
| Comments Histogram | |
| Closest SAT Scores | |
| Top Three Salaries | |
| Prime to N | |
| Compute Deviation |
Synthesized from candidate reports. Individual experiences may vary.
A high-level conversation about your background, interest in the role, and overall fit. This first touchpoint is used to align on role expectations before moving into interviews with the hiring team.
You discuss your background, the role, stakeholder landscape, and behavioral scenarios with the hiring manager. Expect situational questions about managing stakeholder conflicts, using technical tools to solve business problems, and a deep dive into a past project, with some technical SQL questions mixed in.
A technical director leads a deep SQL and BI interview covering 8-10 questions from easy to hard. Topics include SQL optimization, window functions, and Power BI concepts such as field parameters, dimensions, and measures; some questions may require exact written queries or coding on a platform with test cases.
A final interview loop with three behavioral interviews and one technical interview. The behavioral rounds focus on Chewy’s company principles, and you’re expected to answer using STAR-format stories that demonstrate alignment with those principles.
