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Compliance: HIPAA, GDPR & FedRAMP on GCP

GCP Data EngineeringCompliance⭐ Premium

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Compliance on GCP

Master compliance on GCP including HIPAA, GDPR, FedRAMP, data residency, and compliance frameworks for data engineering.

16 min readIntermediate

Compliance Frameworks

πŸ›‘οΈ GCP Security Architecture for Data Engineering
GCP Security: Defense-in-Depth for Data EngineeringENCRYPTIONAt RestAES-256, auto-rotated by defaultIn TransitTLS 1.2+, internal Google networkCMEKCustomer-managed encryption keysCSEKCustomer-supplied encryption keysVPC SERVICE CONTROLSService PerimetersBoundaries around GCP servicesAccess LevelsIP, device, identity conditionsDry-run ModeTest before enforcementBridge PerimetersCross-perimeter accessCloud Armorβ€’ DDoS Protectionβ€’ WAF Rules (OWASP)β€’ IP Allow/Deny Listsβ€’ Adaptive ProtectionCloud DLP APIβ€’ Data Classificationβ€’ Sensitive Data Detectionβ€’ De-identificationβ€’ InfoType TemplatesCloud KMSβ€’ Key Rings & Keysβ€’ HSM / External KMSβ€’ Key Rotationβ€’ IAM for KeysSHARED RESPONSIBILITY MODELGoogle Manages: Physical security, network, hypervisorYou Manage: Data, IAM, configs, application codeDATA ENGINEERING SECURITY CHECKLISTβœ“ Enable CMEK for BigQueryβœ“ VPC-SC for data projectsβœ“ DLP for sensitive dataβœ“ Audit logs enabled
Interview Tip: GCP follows a shared responsibility model β€” Google secures the infrastructure, you secure your data. Enable encryption at rest (default), use CMEK for sensitive data, implement VPC Service Controls for data exfiltration prevention, and use Cloud DLP to classify and protect PII.

GCP Compliance Features

# Compliance implementation checklist
compliance_checklist = {
    "encryption": {
        "at_rest": "CMEK for sensitive data",
        "in_transit": "TLS 1.2+ (automatic)",
        "key_rotation": "Automated via Cloud KMS"
    },
    "access_control": {
        "iam": "Least privilege principle",
        "vpc_sc": "VPC Service Controls for perimeter security",
        "column_security": "Policy tags in BigQuery"
    },
    "audit_logging": {
        "admin_activity": "Always enabled",
        "data_access": "Enable for sensitive data",
        "log_retention": "Store in separate project"
    },
    "data_residency": {
        "single_region": "Data stays in specified region",
        "dual_region": "Two specific regions",
        "multi_region": "All regions in geographic area"
    }
}

GDPR Implementation

# GDPR data deletion request handler
from google.cloud import bigquery

def handle_deletion_request(project_id, dataset_id, user_email):
    """Handle GDPR right to erasure request."""
    client = bigquery.Client(project=project_id)

    # Find and delete user data across all tables
    tables = client.list_tables(f"{project_id}.{dataset_id}")

    for table in tables:
        query = f"""
        DELETE FROM `{project_id}.{dataset_id}.{table.table_id}`
        WHERE email = '{user_email}'
        """

        try:
            job = client.query(query)
            job.result()
            print(f"Deleted data from {table.table_id}")
        except Exception as e:
            print(f"Error deleting from {table.table_id}: {e}")

    # Log deletion for audit
    log_deletion_request(user_email, dataset_id)

✨

Best Practice: Implement defense-in-depth: encryption (CMEK), access control (IAM + VPC-SC), audit logging, and data classification. Use separate projects for production and non-production. Enable data access audit logs for sensitive datasets. Review compliance configurations quarterly.

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Common Interview Questions

Q1: What are the key GDPR requirements for data engineering?

Answer: 1) Data minimization (collect only necessary data), 2) Purpose limitation (use data only for stated purposes), 3) Storage limitation (delete when no longer needed), 4) Right to erasure (implement deletion requests), 5) Data portability (export user data).

Q2: How does GCP help with HIPAA compliance?

Answer: Google signs BAAs for HIPAA-covered services (BigQuery, GCS, etc.). GCP provides: 1) Encryption at rest and in transit, 2) Audit logging, 3) Access controls, 4) Data processing agreements. Customers must implement additional controls for PHI.

Q3: What is the purpose of VPC Service Controls for compliance?

Answer: VPC Service Controls create security perimeters to prevent data exfiltration. They restrict which services can access sensitive data, control network egress, and provide audit trails for compliance reporting.

Q4: How do you implement data residency requirements?

Answer: 1) Use single-region resources for strict residency, 2) Configure BigQuery dataset locations, 3) Use GCS dual-region buckets, 4) Implement IAM conditions for region restrictions, 5) Monitor and audit data locations.

Q5: What is the difference between encryption at rest and in transit?

Answer: At-rest encryption protects data stored on disk (CMEK or Google-managed keys). In-transit encryption protects data moving between services (TLS 1.2+). Both are required for compliance. GCP provides automatic in-transit encryption; at-rest requires CMEK for customer-managed keys.

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