Chewy Data Analyst Interview Guide

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.