Chewy Data Analyst Interview Questions + Guide in 2025

Chewy is a leading online retailer of pet food and supplies, dedicated to delivering a seamless shopping experience for pet owners and their beloved companions.

As a Data Analyst at Chewy, you will play a critical role in leveraging data to enhance the company’s strategic objectives and customer satisfaction. Your responsibilities will include analyzing large sets of diverse data, creating insightful reports, and developing dashboards that inform decision-making across various departments. You will collaborate closely with cross-functional teams, including product managers and engineers, to identify key performance indicators (KPIs) and develop analytics frameworks that align with Chewy’s growth strategies.

The ideal candidate will possess strong technical skills in SQL, data visualization tools like Tableau, and advanced Excel functions, with a knack for storytelling through data. A background in e-commerce or retail analytics is highly desirable as you will be expected to assess business performance and provide actionable insights that drive financial outcomes. Strong communication skills, both verbal and written, are essential, as is the ability to work independently while fostering collaboration within a team-oriented environment.

This guide will provide you with valuable insights and tailored preparation strategies to help you excel in your interview for the Data Analyst position at Chewy, ensuring you present your skills and experiences effectively.

The interview process for a Data Analyst at Chewy is designed to evaluate technical depth, business judgment, and alignment with Chewy’s leadership principles. Candidates can expect a structured, multi-stage process with increasing emphasis on SQL rigor and behavioral consistency.

Interviews are conducted over Zoom, with a limited or no interactive coding environment for testing SQL queries.

1. Recruiter Screen

The process begins with a recruiter screen focused on background, role expectations, and overall fit. This conversation covers prior experience, interest in Chewy, and alignment with the responsibilities of the role. Candidates should be prepared to clearly explain their career progression and how their experience maps to a BI or analytics-focused position.

2. Technical SQL Assessment

Candidates typically complete a dedicated SQL-focused technical round consisting of 8 to 10 questions ranging from easy to hard. These questions emphasize core query logic, window functions, and optimization concepts. Some questions require writing exact SQL queries without the ability to execute or validate results, increasing the importance of careful reasoning and precision. Time per question is limited, so clarity and efficiency matter.

Note that SQL is tested rigorously and early, even during hiring manager rounds, making it a table-stakes requirement.

3. Hiring Manager Interview

The hiring manager interview usually lasts 45 to 60 minutes and blends behavioral and technical discussion. This round includes deep dives into past projects, how technical tools were used to solve real business problems, and how candidates handled stakeholder conflicts or competing priorities. Interviewers assess both analytical thinking and communication skills.

4. Final Virtual Onsite Loop

The final stage is a single-day virtual onsite loop consisting of four interviews, each approximately 45 minutes long. This loop typically includes three behavioral interviews and one technical interview. Across all sessions, there is a strong emphasis on Chewy leadership principles, with candidates expected to consistently map real work experiences to those principles rather than providing generic behavioral answers.

Overall, candidates are evaluated not only on technical correctness but also on their ability to reason clearly, explain decisions, and demonstrate principled decision-making across the entire interview process.

Here are some tips to help you excel in your interview.

Understand the Competitive Landscape

Given that the interview process at Chewy can be quite competitive, it’s crucial to familiarize yourself with the company’s position in the e-commerce and pet care market. Research Chewy’s recent initiatives, partnerships, and any challenges they may be facing. This knowledge will not only help you answer questions more effectively but also demonstrate your genuine interest in the company and its mission.

Prepare for Behavioral Questions

Chewy places a strong emphasis on behavioral interviews, so be ready to discuss your past experiences in detail. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Highlight specific projects where you made a significant impact, particularly those that involved data analysis and decision-making. Be prepared to discuss how your work has influenced revenue or improved processes, as this aligns with what Chewy values in candidates.

Showcase Your Technical Skills

Technical proficiency is a must for a Data Analyst role at Chewy. Brush up on SQL, Tableau, and Excel, as these tools are frequently mentioned in the interview process. Be ready to solve practical problems or case studies during the interview, as candidates have reported being asked to demonstrate their technical capabilities. Practice common SQL queries and data visualization techniques to ensure you can showcase your skills effectively.

Communicate Clearly and Confidently

Effective communication is key, especially when presenting complex data insights. Practice explaining your analytical findings in a clear and concise manner, as you may need to present your insights to non-technical stakeholders. Tailor your communication style to your audience, ensuring that you can convey technical information in an accessible way.

Emphasize Collaboration and Leadership

Chewy values cross-functional collaboration, so be prepared to discuss how you’ve worked with different teams in the past. Highlight any leadership experiences, even if informal, where you guided a project or mentored others. Demonstrating your ability to work well with diverse teams will resonate with Chewy’s culture of collaboration.

Be Ready for Case Studies

Expect to encounter case study questions that require you to analyze a business scenario and provide actionable insights. Practice structuring your thought process and articulating your reasoning. Focus on how you would approach the problem, the data you would need, and the metrics you would use to measure success.

Follow Up with Questions

At the end of your interview, take the opportunity to ask insightful questions about the team, the analytics tools they use, or the challenges they face. This not only shows your interest in the role but also helps you gauge if Chewy is the right fit for you. Tailor your questions based on your research about the company and the specific team you are interviewing with.

By following these tips, you can position yourself as a strong candidate for the Data Analyst role at Chewy. Good luck!

In this section, we’ll review the types of interview questions candidates may encounter during a Data Analyst interview at Chewy. The interview process evaluates SQL depth, BI fundamentals, business thinking, and the ability to communicate clearly with stakeholders. Candidates should be prepared to explain their reasoning, not just produce correct answers.

Technical Skills

1. Describe a SQL query you wrote that had a meaningful business impact

   This question assesses practical SQL experience and how analysis translates into real business decisions. Interviewers look for a clear explanation of the problem, the logic behind the query, and the measurable outcome of the work.

2. How would you optimize a slow-running SQL query?

   This question evaluates your ability to diagnose performance issues and reason about efficiency. Interviewers expect discussion around indexing, join strategy, query restructuring, and tradeoffs rather than just surface-level fixes.

3. Explain the difference between inner joins and outer joins in SQL

   This question tests foundational SQL knowledge and understanding of how joins affect result sets. Interviewers look for clarity on when each join type is appropriate in real analysis scenarios.

4. What key metrics would you track for an e-commerce business like Chewy?

   This question assesses business context and analytical judgment. Candidates are expected to connect metrics to customer behavior, growth, retention, and operational performance rather than listing metrics in isolation.

5. Explain the difference between dimensions and measures in Power BI

   Candidates are asked to explain how dimensions and measures differ in Power BI and how each is used in reports. Interviewers look for a clear explanation of aggregation behavior and how incorrect modeling choices can lead to misleading or incorrect dashboards.

6. How would you use Power BI field parameters to support dynamic reporting?

   This question evaluates practical Power BI knowledge used in stakeholder-facing dashboards. Candidates are expected to explain how field parameters allow users to dynamically switch metrics or views without duplicating visuals.

Behavioral Questions

1. Tell me about a time you analyzed data under a tight deadline

   This question evaluates time management, prioritization, and decision-making under pressure. Interviewers look for how candidates scoped the problem and focused on high-impact analysis.

2. How do you ensure the accuracy of your analysis?

   This question tests analytical rigor and attention to detail. Candidates should demonstrate a structured approach to validation, checks, and confidence in their results.

3. Describe a time you had to explain complex data to a non-technical stakeholder

   This question assesses communication skills and business translation. Interviewers want to see how candidates simplify insights and tie data back to decisions.

4. Tell me about a project you are most proud of

   This question allows candidates to demonstrate ownership, impact, and end-to-end thinking. Interviewers look for clarity on the candidate’s role and the results achieved.

5. How do you handle competing priorities from multiple stakeholders?

   This question evaluates judgment, collaboration, and expectation management. Candidates should show how they balance urgency, impact, and communication in real work settings.