Databricks Data Scientist Interview Questions

900+ verified questions, indexed by team and level. Real questions submitted by candidates who completed Databricks loops in the last 24 months.

About the Databricks Data Scientist hiring loop

Databricks interviews are unusually deep on distributed-systems and big-data internals (Spark, Delta Lake, MLflow). Coding rounds are LeetCode-medium-to-hard, system design dives into lakehouse architecture, and behavioural rounds score "Customer Obsession + Truth-Seeking".

Data Science rounds score on statistical rigour, metric definition quality, SQL fluency, framework clarity for case studies, and communication of uncertainty. Companies weight experimental design vs ML modelling differently.

Topics covered in Databricks Data Scientist interviews

  • 01Probability + statistics (hypothesis tests, A/B testing, p-values)
  • 02SQL fluency under time pressure
  • 03Machine learning fundamentals (bias-variance, regularisation, evaluation metrics)
  • 04Experimental design (sample size, power, interference)
  • 05Analytical case studies with metric definition
  • 06Stakeholder communication of statistical results

Practice Databricks Data Scientist questions with the AI copilot

Interview Lift's mock interview simulator pulls from the same 900+ verified bank above. Run a full Databricks Data Scientist loop with AI interviewer voice + per-answer scoring + transcript debrief. 7-day free trial, no credit card.

Other Databricks roles

Data Scientist questions at other companies