You will work closely with the Data Governance team to translate business and legal requirements into automated technical controls within our Lakehouse and BigQuery ecosystem.

Core Responsibilities :

Data Privacy & Security (DLP/RLS) :

- Automated DLP : Implement Cloud DLP (Data Loss Prevention) to automatically detect, classify, and mask PII/Sensitive data across the Lakehouse.

- Access Control : Build and manage Policy Tags and Row Level Security (RLS) in BigQuery based on user attributes and data sensitivity.

- WIF & Identity : Integrate Workload Identity Federation (WIF) to ensure secure, keyless authentication for all data workloads.

Data Quality & Validation Frameworks :

- Quality-as-Code : Build a scalable framework for Data Quality Rules (using dbt tests, Great Expectations, or Soda) including dashboards for data health scores and automated remediation.

- Model Validation : Implement automated checks to ensure all new data products align with the Universal Data Model (UDM) and Master Data Management (MDM) consistency rules.

Compliance & Lifecycle Automation :

- Retention & Cleaning : Automate Data Retention Policies (expiration, cold archiving, and permanent deletion) to comply with data protection laws (GDPR/LGPD).

- Metadata & Cataloging : Integrate platform metadata with Dataplex and the Universal Metadata Catalog (MFW) to ensure 100% lineage and ownership visibility.

- Discovery : Implement repository scanning to discover hidden data assets and cross-domain dependencies.

Technical Requirements (Must-Have) :

- GCP Data Stack : Expert knowledge of BigQuery, Dataplex, Cloud DLP, and IAM/RBAC structures.

- SQL : Expert level.

You must be able to build complex validation

- Python : Proficiency in building automation scripts for metadata extraction and lifecycle management.

- Data Governance Tools : Experience with Data Catalogs (Collibra, Atlan, or Dataplex) and Business Glossaries.

- Compliance Knowledge : Practical understanding of Data Privacy laws and how they translate to technical "Hard Deletes" or "Anonymization."

Specific Deliverables (Based on Platform Roadmap) :

- Unified Metadata Sync : Automate the metadata flow from MFW to Dataplex.

- Data Product Catalog : Build the technical backend for the "Data Product Catalog," including automated SLA tracking and lineage.

- Governance Dashboard : Create a "Health Score" dashboard for the CFO/CDO showing compliance percentages for DLP and Data Quality across all domains.

The "Plus" List :

- Arcop Integration : Experience integrating with Arcop for corporate data management.

- Infrastructure as Code : Experience using Terraform to deploy security policies and IAM roles.

- AI/ML for Governance : Using ML to automate the discovery of undocumented PII