Interview questions
Preparing for a data engineering interview at Bristol Myers Squibb? This page contains 5 real interview questions sourced from verified Bristol Myers Squibb interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
Bristol Myers Squibb data engineering interviews typically focus on SQL, and Spark/Big Data. 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.
Write a query to find the top three highest-paid employees in each department using window functions.
Explain the architectural trade-offs when optimizing a query on 100M+ rows: indexing vs. partitioning vs. materialized views. When does each approach become cost-prohibitive or operationally burdensome, and how do you quantify impact?
How would you handle nulls in a SQL join? Provide examples using COALESCE.
Write PySpark code to filter records based on specific conditions and add a calculated column.
Write a PySpark script to filter out invalid records from a dataset and calculate the average for a specific column, ensuring the schema is strictly defined at runtime.
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