Data Governance Architect III

Overview

Why GMF Technology? Innovation isn’t just a talking point at GM Financial—it’s how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We’re committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry.

Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact.

We are not able to provide visa sponsorship either now or in the future for this role.

As regulatory expectations increase, governance must move from advisory to engineered. The Data Governance Architect provides a single point of accountability to embed compliance into how data is designed, shared, protected, and audited—reducing risk, audit findings, and operational inefficiency while increasing trust in enterprise data.

The Data Governance Architect III is accountable for designing and operationalizing enterprise data governance to ensure regulatory compliance, audit readiness, and trusted data management s role embeds governance policies—definitions, metadata, lineage, classifications, quality, and access controls—directly into data architecture, cloud platforms, and delivery practices.

• Design and maintain enterprise data governance architecture
• Translate regulatory and business policies into enforceable standards
• Lead definition and maintenance of data standards (naming, modeling, metadata, classification, quality, lineage, access controls)
• Govern canonical definitions, taxonomies, and semantic standards
• Architect and govern enterprise metadata management, including business, technical, operational, and privacy metadata
• Ensure traceability from logical model → canonical model → physical data → consumption
• Architect governance controls that support:
  Data mapping and Records of Processing (RoPA), privacy classification, purpose limitation, and retention; DSAR discovery, impact analysis, and execution
• Lead governance architecture and integration for platforms such as:
  Informatica CDGC / CDQ, BigID, Service Now
• Integrate governance tooling with:
  Cloud data platforms, ETL/ELT tools, BI and analytics tools (Power BI)
• Provide guidance on master data, reference data, and interoperability across systems and platforms
• Establish data-sharing contracts and domain service agreements to ensure consistent use of data across the enterprise
• Influence architecture decisions to ensure data governance requirements are embedded into product and platform designs
• Align governance with cybersecurity controls
• Ensure governance controls align with compliance requirements (SOX, GDPR, CCPA, HIPAA, PCI, etc.)
• Support integration and traceability between data architecture and enterprise architecture (capability maps, application/technology portfolios)

• High School Diploma or equivalent required
• Bachelor’s Degree in related field or equivalent work experience preferred
• 4-6 years experience in data modeling, data architecture, data governance or enterprise data management required
• Strong knowledge of data governance frameworks (e.g., DAMA‑DMBOK) and data management practices
• Expertise in data modeling (conceptual/logical/physical), metadata, and taxonomy/ontology design
• Familiarity with privacy regulations (e.g., GDPR, CCPA) and compliance standards; experience partnering with Privacy/Compliance
• Experience with enterprise architecture frameworks (e.g., TOGAF) and architecture governance
• Excellent stakeholder management and communication skills; able to influence without authority across business and technology
• Experience with regulatory data management and tools like BigID or One Trust is a plus
• Practical experience implementing MDM, data catalogs, and lineage (e.g., Informatica CDGC, Collibra, Alation, Azure Purview)
• Modeling tools (e.g., ER/Studio, Erwin)
• Knowledge of security and risk frameworks (e.g., NIST, ISO 27001) and data protection techniques (tokenization/masking)
• Backgr…