Data Analyst interview: technical and business questions
Data Analyst interviews combine technical foundations with business reasoning.
Do not prepare syntax alone. Employers want to see how you turn an ambiguous question into reliable analysis and a useful recommendation.
What Data Analyst interviews assess
Expect analytical reasoning, SQL, data quality, basic statistics, visualisation and business communication.
Check whether the role is closer to product, operations, marketing, finance or reporting.
SQL questions
Practise joins, aggregations, window functions, CTEs, subqueries, null handling and duplicates.
Explain assumptions and how you would validate the result.
Statistics and experimentation
Review distributions, correlation, confidence intervals, significance and A/B tests according to the role.
Prioritise interpretation over memorised formulas.
Business and metrics questions
A case may involve falling conversion, higher churn or a changing metric.
Clarify definitions, segment the problem and form hypotheses before asking for data.
Case studies and take-home tasks
Document assumptions, clean the data, prioritise questions and build a narrative.
Include limitations and separate evidence from inference.
Communicating results
Lead with the conclusion and add only the evidence the audience needs.
Be ready to defend assumptions and change your view when better evidence appears.
Questions for the data team
Ask which decisions the team supports, data quality, tooling and how requests are prioritised.
Clarify the balance between exploratory analysis and recurring reporting.
Practical preparation tips
- ✓Practise SQL while explaining assumptions.
- ✓Review statistics through interpretation.
- ✓Train business cases.
- ✓Prepare a project where analysis changed a decision.
- ✓Practise explaining findings to a non-technical audience.
Put it into practice
Practise a Data Analyst interview
Train SQL, business reasoning and communication questions in a simulation adapted to the role.
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