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ThoughtWorks Data Engineer Interview Questions

The questions to prepare for a ThoughtWorks Data Engineer interview. Questions from real interview reports rank first. Updated weekly.

Batch vs Streaming Data ProcessingEasy

Compare batch and streaming data processing, including when each fits best in a pipeline.

Stream ProcessingETLBatch Processing
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Handle PySpark Data Skew
Medium

Approach for detecting and mitigating skew in PySpark pipelines using partitioning, join strategies, and runtime monitoring.

Data Qualitypysparkdata skewness
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Data Quality in ETL Pipelines
Easy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQuality
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Parquet vs Avro vs ORC
Medium

Evaluates your understanding of storage formats and how they impact performance and usability.

parquet
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Testable and Maintainable Pipelines
Medium

Evaluates your approach to building maintainable, verifiable data pipelines.

maintainabilityPipelines
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Disagreeing on a Technical Direction
Medium

Tests conflict resolution and influence during technical disagreement, including how you challenge decisions and commit after alignment.

Influence Without AuthorityConflict Resolutionteamwork
Recently asked
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Live Coding in PySparkHard

Tests your ability to implement PySpark solutions while applying TDD principles under time pressure.

pyspark
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SQL, Python, and PySpark Work
Medium

Tests your ability to apply SQL and PySpark concepts to real data transformation work.

pysparksqlpython
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