Data analyst interviews test SQL and statistics, but above all whether you can turn data into a decision someone acted on. Below are the questions you're most likely to face and what a strong answer shows. When you're ready, rehearse them in the Interview Lab with questions built from your job ad.
What they're looking for
The question, the method, the insight, and the decision and impact that followed.
What they're looking for
Window functions (RANK or ROW_NUMBER with PARTITION BY), handling ties, and checking the result.
What they're looking for
Profiling first, then deciding whether to impute, exclude or flag, and documenting your assumptions.
What they're looking for
Simple language, the "so what" first, and visuals that support one message.
What they're looking for
Check the data pipeline first, then segment by dimension, find the timing, and form hypotheses.
What they're looking for
Line charts for trends, bar charts for comparisons, and avoiding chart junk.
Most candidates know the questions and still freeze on the day. In the Interview Lab, an AI hiring manager asks questions written from the real job ad and your CV. You answer by voice or text and get a scored report with a stronger version of every answer.
Start with a free match checkStudy the job ad, prepare STAR stories for the competencies it lists, rehearse answers out loud, and do a mock interview. The Interview Lab generates data analyst questions from the actual ad and scores your answers.
Roughly 1 to 2 minutes for behavioural questions. Technical questions can run longer if you walk through your reasoning.