McKinsey & Data Engineer Interview Questions
The questions to prepare for a McKinsey & Data Engineer interview. Questions from real interview reports rank first. Updated weekly.
Explain when to use PySpark map versus flatMap, with examples that show one-to-one and one-to-many transformations.
McKinsey &Approach for handling schema changes and data quality checks in a high-volume data lake pipeline.
McKinsey &Optimize a PySpark join when one DataFrame is much smaller, focusing on join strategy, shuffle reduction, and practical Spark tuning.
McKinsey &Tests influence without authority in a high-stakes disagreement with a senior stakeholder, including communication, conflict handling, and outcome ownership.
McKinsey &Calculate each customer's cumulative transaction amount over time using a CTE and window function.
McKinsey &Find the first character in a string that appears exactly once using a hash table in linear time.
McKinsey &Use recursive traversal to flatten nested JSON objects and arrays into path-based key-value pairs.
McKinsey &Tests your query tuning approach for performance and correctness on partitioned datasets.
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Aggregate customer sales volume and return Pyramid Consulting's top 10 customers in descending order.
Pyramid Consulting
BNY
Cambia Health SolutionsUse JOIN, GROUP BY, and HAVING to find the top three departments by average salary with at least five employees.
Paylocity
Booz Allen Hamilton
Nashville Staffing