HackerRank Data Engineer Interview Questions
The questions to prepare for a HackerRank Data Engineer interview. Questions from real interview reports rank first. Updated daily.
Use PostgreSQL joins and aggregation to expose missing candidates, tests, submissions, and NULL join values.
Translate PySpark DataFrame transformations into PostgreSQL SQL using joins, ranking, lag values, and cumulative totals.
Use CASE, RANK, LAG, and LEAD to classify records and compare ordered values within categories and entities.
Aggregate values by key and return the top k totals using a hash map and deterministic sorting.
Count words or characters across text chunks using a dictionary while preserving chunk boundaries for word mode.
Flatten nested HackerRank JSON objects and arrays, then return values for requested dotted paths.
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Explain Spark execution internals, transformation lineage, actions, shuffles, and performance tuning decisions.
Diagnose a slow Spark job with Spark UI, identify the bottleneck, and apply targeted performance improvements.