Technology · 10 questions

    Data Analyst screening interview questions

    The best analysts combine technical fluency with business judgment. A screen should confirm the candidate can query data independently, communicate findings plainly, and knows when the data is wrong.

    Last reviewed 2026-09-10

    What a good data analyst screen should establish

    • Practical SQL and spreadsheet or BI tool experience
    • Translating business questions into analyses
    • Data quality skepticism
    • Clear communication of findings to non-technical stakeholders
    • Impact: analyses that changed a decision

    The questions, and what to listen for

    1. 01

      Tell me about an analysis that changed a business decision.

      Listen for: A clear question, method, finding, and the decision that followed.

    2. 02

      How comfortable are you with SQL? Describe the most complex query you have written for real work.

      Listen for: Joins, window functions, CTEs; explains the business purpose.

    3. 03

      A stakeholder asks for 'a dashboard on sales.' What do you do first?

      Listen for: Clarifies the decision they need to make and the metrics that matter.

    4. 04

      Tell me about a time the data was wrong. How did you notice?

      Listen for: Sanity checks, reconciliation against known totals, validating pipeline assumptions.

    5. 05

      How do you present findings to executives?

      Listen for: Leads with the answer, one chart per point, avoids jargon.

    6. 06

      Which BI or visualization tools have you used, and which do you prefer?

      Listen for: Real experience with tools such as Tableau, Looker, Power BI, plus reasoning.

    7. 07

      How do you prioritize when multiple teams need analyses this week?

      Listen for: Asks about impact and urgency, communicates trade-offs, avoids silent overcommitment.

    8. 08

      Describe a metric definition that caused confusion and how you resolved it.

      Listen for: Documented definitions, aligned stakeholders, single source of truth.

    9. 09

      What is your experience with Python or R for analysis?

      Listen for: Honest self-assessment; not required for every analyst role.

    10. 10

      What do you do if the analysis does not support what the stakeholder hoped for?

      Listen for: Reports honestly with context; suggests next steps.

    Red flags

    • Cannot describe an analysis that led to a decision
    • Treats stakeholder requests literally without asking why
    • No instinct for checking data quality

    Data Analyst screening FAQ

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