ETL Testing for Modern Data Engineering: A Shift-Left SDET Approach

Chiranjeevulu Reddy Kasaram

doi:10.15662/IJRAI.2024.0706028

Authors

Chiranjeevulu Reddy Kasaram Independent Researcher, USA Author

DOI:

https://doi.org/10.15662/IJRAI.2024.0706028

Keywords:

ETL testing, Python, data validation, automation, data quality

Abstract

The transformation of the quality assurance role into that of the Software Development Engineer in Test (SDET) has redefined expectations for modern data engineering workflows. In data-driven systems, user interfaces represent only the surface layer of complex data pipelines, making Extract-Transform-Load (ETL) testing a critical component of quality assurance. This paper explores Python-powered ETL testing pipelines as a foundation for automating data validation within the SDET workflow. Emphasizing a shift-left testing philosophy, we propose early and continuous validation of transformation logic, data models, and full ETL processes to ensure completeness, consistency, and timeliness of data. By leveraging Python, advanced SQL, and CI/CD integration, SDETs can design reusable, scalable, and maintainable validation systems that uphold data governance principles and provide sustained data integrity across analytical and operational contexts.

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