Data Engineering Interview Questions and Answers: Part 1 | Python, Pandas, SQL and DuckDB
Summary : Prepare for data engineering interviews with practical questions and answers covering Python, Pandas, DuckDB SQL, data validation, aggregations, window functions, and reproducible data pipelines. This Part 1 guide includes two hands-on coding challenges: finding the top three users by monthly spending and verifying that Pandas and SQL return equivalent results. Introduction Preparing for a data engineering interview involves more than writing code that produces the correct output. You should also be able to explain your approach, validate assumptions, identify edge cases, and demonstrate that your results are reliable. This guide covers essential data engineering concepts through practical questions and coding exercises. You will explore reusable Python functions, data-quality checks, Pandas transformations, DuckDB SQL queries, aggregations, and window functions. You will also solve two hands-on problems. The first identifies the top three users by total spending for ...