Interview questions
Preparing for a data engineering interview at Gartner? This page contains 34 real interview questions sourced from verified Gartner interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
Gartner data engineering interviews typically focus on SQL, Python/Coding, and System Design/Architecture. There's a solid mix of fundamental and advanced questions, making it accessible for candidates at multiple experience levels.
Use the difficulty filters above to focus your preparation. For each question, attempt your own answer first, then compare with our expert solution. You can also practice these questions in our AI Mock Interview Coach for real-time feedback.
How do you handle disagreement with a co-worker?
How do you handle lack of communication from stakeholders?
How would you convince stakeholders to move from Google Drive to Amazon S3?
Tell me about yourself apart from CV.
Explain your job to a kid.
How do you deal with failed large file processing when a file fails at the final 10%?
How do you handle fluctuations in active users?
Compare compression algorithms: Gzip vs Snappy.
Create a dictionary with list elements as keys and their occurrences as values.
Explain Lambda functions in Python.
Explain this code: [f(2) for f in [lambda x: x * i for i in range(5)]].
Write a swap function without if-else.
Compare PostgreSQL vs Snowflake. How do they handle duplicate record errors?
Explain ETL process flags and segregation of steps.
Explain Union vs Union All in SQL.
Explain normalization and its disadvantages.
Explain peer code review and team lead review.
Explain the difference between a clustered and non-clustered index.
Explain the difference between a fact table and a dimension table.
Explain the difference between a primary key and a unique key.
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