What’s the practical difference between GDPR and CCPA for engineering?

Both want minimization, protection, and user rights. GDPR leans heavier on lawful basis and storage limitation; CCPA emphasizes disclosure/opt-out and has a 45-day DSAR timeline (extendable). Implement the same guardrails: tag data, block risky infra, mask/encrypt, automate deletions, and produce evidence. Tailor consent and regional routing to legal guidance.

How do we handle DSAR (access/deletion) at scale?

Index where user identifiers live via your data map; build scripts to fetch/delete across systems with dry-run. Use job queues and rate limit deletes. Emit signed evidence of each DSAR action with request ID and timestamps. Aim for one-click runs from a service account, not human consoles.

Do we need a data catalog to start?

You need tags and a minimal inventory, not a six-month catalog rollout. Start with OpenMetadata or even YAML in Git that services reference. You can graduate to BigID/Collibra later—just don’t skip tagging and propagation.

Are masking policies enough without encryption?

No. Masking protects views/queries; encryption protects at-rest theft scenarios and key management. You want both: SSE-KMS (or TDE/field-level) plus masking/row policies. Also minimize: don’t collect what you can’t protect.

Security-compliance · Dec 9, 2025 · 10 minute read

Stop Hand-Waving Privacy: Turn GDPR/CCPA Into Guardrails Your Pipeline Enforces

Compliance isn’t a PDF in Confluence. It’s a failing build, a masked column, and an auditable proof. Here’s how to translate GDPR/CCPA into automated checks without grinding delivery to a halt.

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Stop Hand-Waving Privacy: Turn GDPR/CCPA Into Guardrails Your Pipeline Enforces

Key takeaways

Implementation checklist