Data Engineers: Privacy Is Your Problem
summary
Argues that data engineers must own privacy by building a metadata-driven access layer that abstracts governance from each warehouse and app, using tools like Immuta policy engine to push consistent masking, row-level security and context-aware rules across platforms. Recommends tagging direct identifiers, applying k-anonymization or differential privacy where needed, and using purpose-based access (users switch purposes to gain different views). Shows masked-column rule that returns null except under a declared purpose and claims this scales across vendors.
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chapters (5)
- 0:00Introduction to data governance
- 1:51Steam engine analogy and data parallels
- 8:31Key players in data governance
- 15:56Metadata-driven governance solutions
- 26:57Future of connected data ecosystems
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