Your question is Building Trusted Data Pipelines Across Sources. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How to handle complex data scattered across various data sources during data integration?
Asked in the Technical interview stage. 2-person panel.
Treat this as a practical system design exercise. Explain how you would inventory heterogeneous sources, ingest batch and streaming data, reconcile schemas and entities, validate quality, manage lineage and access controls, and publish trusted datasets for ML training and inference. Clarify missing scale, freshness, latency, retention, and compliance requirements before choosing technologies. Discuss failure handling, replayability, monitoring, and how to prevent training-serving skew.