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Google Cloud Certified Professional Data Engineer · Google Cloud
Select one answer.
Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.
A. Viewer role: Still exposes all resources and metadata in the project, too broad. B. Dataflow Developer role: Lets them run pipelines on the real project (and potentially access private data). C. Service account sharing: A security anti-pattern; violates identity/accountability. D. Anonymized sample in a separate project: Safest and compliant option—consultant can code and test transformations without ever seeing sensitive data.
I think only D really covers user's privacy
You’re dealing with sensitive user data (possibly PII or other regulated content). Principle of least privilege and data minimization are key. External consultants should never be given access to production data unless absolutely necessary — and in this case, it's not. Creating an anonymized or synthetic dataset lets them do their work (e.g., test code or build transformations) without compromising real user data. Using a separate project also provides better audit boundaries and isolation.