Data Science and Data Engineering Interview Questions

Data interviews combine SQL and coding, statistics or modelling for data scientists, pipelines and data modelling for data engineers, and behavioural questions about working with stakeholders and turning analysis into decisions.

Below are 20 questions asked in data science and data engineering interviews, each with a sample answer and tips. Read the answer, then practise it out loud: InterviewGuru's AI mock practice scores your spoken or typed answer out of 10 and shows what to improve.

🎯 What interviewers look for
  • Framing a business question as an analysis or a metric before reaching for a model
  • Statistics you can explain simply: experiments, significance, bias and leakage
  • Pipelines that are reliable: batch versus streaming, idempotent jobs, data quality checks, schemas
  • Trade-offs between accuracy, latency, cost and interpretability
  • Stories where your analysis changed a decision, and how you communicated uncertainty
Job Offer Negotiation (2)
Product Sense (2)
System Design (6)
Technical (7)
Coding (3)

Practise out loud with AI feedback

Answer any of these questions by voice or text and get a score out of 10 with strengths and improvements.

📚 Questions for other roles