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GCP Professional Data Engineer Practice Question

Your organization runs a nightly Python ETL on a managed instance group of Compute Engine VMs. The code must read objects from a Cloud Storage bucket (gs://raw-sales) in project-data and write results to the analytics.sales BigQuery dataset in project-analytics. Security mandates that no human credentials or static keys reside on the VMs, access follows least privilege, and credentials rotate automatically without rebuilding images. Which solution best satisfies all requirements?

  • Store an OAuth 2.0 refresh token for a privileged developer account in Secret Manager and have the ETL retrieve it on startup to authenticate to Cloud Storage and BigQuery.

  • Generate a JSON key for a new service account with Storage Admin and BigQuery Admin roles, copy the key to each VM, and configure the ETL to use it via the GOOGLE_APPLICATION_CREDENTIALS environment variable.

  • Create a dedicated service account, grant it Storage Object Viewer on gs://raw-sales and BigQuery DataEditor on analytics.sales, and attach that account to the VM instances so they obtain short-lived tokens from the metadata server at runtime.

  • Grant the Compute Engine default service account the Project Editor role on both projects so the VMs automatically inherit all necessary permissions.

GCP Professional Data Engineer
Designing data processing systems
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