How to Test Data Pipelines Without Trusting the Output
from Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering Hosted by Fexingo
In this episode of Software Testing with Fexingo, Lucas and Luna tackle one of the most frustrating problems in modern data engineering: knowing whether your data pipeline is actually producing correct results. They open with a real-world story about a financial services firm that discovered a silent currency-conversion bug in its reporting pipeline — a bug that had been live for six months and had already influenced client reports. From there, they break down why traditional testing approaches fail for data pipelines, and introduce a practical framework built around data contracts, schema validation, and profiling checks that run on every batch. They walk through a concrete example using a simple e-commerce order pipeline, showing how to write expectations that catch anomalies before they reach dashboards. You'll learn how to test not just the code, but the data itself, and how to build trust in systems that otherwise look fine while quietly corrupting decisions. No fluff, just actionable techniques you can apply to your own pipelines. This episode is a must-listen for data engineers, QA professionals, and anyone who's ever stared at a dashboard and wondered if the numbers are real. #DataPipelineTesting #DataQuality #DataContracts #SchemaValidation #DataProfiling #TestAutomation #QA #SoftwareTesting #DataEngineering #ETL #BatchProcessing #AnomalyDetection #Tech #Business #FexingoBusiness #BusinessPodcast #ReliableSoftware #DataTesting Keep every episode free: buymeacoffee.com/fexingo
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