Do we need a new platform to get compliant?

No. Start with metadata and policy-as-code. Use your warehouse’s native features (Snowflake masking, BigQuery policy tags) and add CI guardrails. We rarely recommend ripping out your lake/warehouse unless it’s fundamentally missing column-level controls.

How do we handle free-text PII in event payloads?

Don’t. Tokenize or hash at the edge. If you must ingest, route into a quarantine dataset with strict policies and a scrubbing job. Flag via lints and pattern scans (DLP) and block the fields from flowing into analytics models.

What about data scientists who need raw PII for model training?

Create purpose-bound sandboxes with time-boxed access and masked defaults. Require a ticket with documented legal basis. Snapshot datasets with row/column policies applied; log all queries. Revoke automatically after the window ends.

Will masking slow down our dashboards?

Usually not. Native masking policies are evaluated at query time and push down efficiently. If you see hotspots, precompute masked views for BI and reserve unmasked tables for narrow roles.

Data-engineering · Nov 7, 2025 · 9 minute read

Ship Dashboards, Not Subpoenas: Standing Up Privacy Controls Without Killing Your Data Pipeline

The playbook we've deployed in regulated shops to meet GDPR/CCPA/HIPAA while keeping reliability, quality, and velocity high.

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Ship Dashboards, Not Subpoenas: Standing Up Privacy Controls Without Killing Your Data Pipeline

Key takeaways

Implementation checklist