Data Product & Asset Governance Associate Director

EY; Dallas (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

EY in Dallas is seeking an experienced Data Product & Asset Governance Associate Director to lead governance for enterprise data products and assets. You will partner with business and technology stakeholders to define ownership, metadata, quality, lineage and access controls across the data lifecycle.

You will apply product management practices to discover, prioritise, roadmap and deliver governance capabilities, ensuring measurable business value and compliance with enterprise standards.

Qualifications

• Bachelor’s degree or equivalent in a technical field essential.
• 8+ years across data governance, data products or AI enablement.
• Experience establishing governance adopted by business and tech teams.
• Hands-on governance platform implementation and workflow configuration.
• Ability to translate governance needs into technical specs and stories.

Responsibilities

• Define governance model for enterprise data products and assets.
• Create governance baselines for metadata, lineage and quality.
• Design workflows for registration, onboarding and sharing.
• Translate policy requirements into machine-readable rules and schemas.
• Deliver governance configurations with stakeholder coordination.

Skills

Data governance

Product management

Stakeholder engagement

Cloud data platforms

SQL scripting

Education

Bachelor’s degree

Tools

Microsoft Purview

Databricks Unity Catalog

Microsoft Fabric/OneLake

Collibra

Informatica IDMC

Alation

Atlan

Job description

Data Product & Asset Governance Associate Director

Other locations: Anywhere in Region

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Position Summary:

The Data Product and Asset Governance SME is an Associate Director role within the Global Data Stewardship Office, combining data governance expertise, hands-on technical implementation and product management skills. The role works with business and technology stakeholders to make enterprise data products and assets trusted, discoverable and reusable throughout their lifecycle. It defines requirements for purpose, ownership, metadata, classification, quality, lineage, access, permitted use, retention and evidence, including fitness for analytics and AI. It translates these requirements into practical standards, metadata models, workflows, quality rules, platform integrations and technology-enabled controls that support federated stewardship. Using product management practices, the role takes producer, consumer and steward needs from discovery and prioritisation through roadmap and backlog definition, design, configuration, testing, approved release and adoption, measuring business value and control effectiveness. Delivery is scoped to approved architecture, security and delivery parameters. Data Owners and product teams remain accountable for their data and outcomes; designated platform and control owners retain enterprise architecture, security approval, infrastructure and production operations accountabilities.

Essential Functions of the Job:

• Define the governance model for enterprise data products and assets, including ownership, stewardship, decision rights, lifecycle stages and evidence requirements.
• Establish a common governance baseline covering business purpose, authoritative source, metadata, classification, quality, lineage, access, permitted use, retention and monitoring.
• Create proportionate governance pathways based on asset type, risk, use, consumer and platform.
• Define criteria for product entry, certification, publication, service, health, change and retirement.
• Define data contract responsibilities between producers and consumers, including service expectations, quality thresholds, permitted use and sharing obligations.
• Design, configure and validate workflows for registration, onboarding, discovery, access approval, sharing, reuse, certification, change and decommissioning, including accountable decisions, exceptions, escalation and auditable evidence.
• Conduct discovery with business stakeholders, Service Line Quality, data producers, consumers and Regional Data Stewards; translate their needs into governance capability roadmaps, prioritised backlogs, user stories and functional and non-functional requirements. Agree priorities and dependencies with the Global Data Office, CTOs, CIOs and relevant product and platform owners.
• Embed governance checkpoints and measurable acceptance criteria into discovery, design, build, release and operation; execute configuration and integration testing, coordinate user acceptance testing, resolve defects and prepare release, rollback and support documentation for approved deployment.
• Evaluate governance platform capabilities and deliver proofs of concept and scoped implementations for catalogues, data marketplaces, metadata, lineage, quality and workflows; configure metadata models, certification criteria and approved rules, and implement supported API, connector or scripting-based integrations within authorised environments.
• Translate approved policy and business requirements into traceable, machine-readable governance rules and metadata; validate discovery outputs with accountable owners and make trusted ownership, classification, lineage and permitted-use metadata available to downstream controls and monitoring.
• Assess product and asset health and define measures for adoption, trust, reuse, risk and value.
• Resolve ownership, authoritative source, product boundary, metadata, quality and control gaps with accountable stakeholders.

Analytical/Decision Making Responsibilities:

• Exercises the judgement expected of an Associate Director when ownership, product boundaries, authoritative sources, quality expectations or permitted uses are unclear or disputed.
• Frames the business decision and risk, maps the product or asset lifecycle and dependencies, identifies accountable owners and consumers, and defines a proportionate target state.
• Balances speed, reuse, business value, trust and risk when setting governance requirements and sharing pathways.
• Recommends authoritative products, ownership models, semantic definitions, quality thresholds, certification criteria and transition actions where multiple or conflicting assets exist.
• Assesses implementation options, platform constraints, integration dependencies, maintainability and control effectiveness; selects configuration and automation approaches within approved patterns and defines interim governance and evidence where capability gaps remain.
• Takes responsibility for the design, configuration, integration, testing and implementation evidence of assigned governance capabilities within delegated authority. Escalates decisions requiring policy, Data Owner, risk, enterprise architecture, security or platform approval; does not assume Data Product Owner or Technology Product Owner accountabilities, infrastructure ownership or production operations responsibility.

Knowledge and Skills Requirements:

• Deep expertise in modern data governance, federated operating models, data domains, ownership, stewardship and decision rights.
• Strong knowledge of data product and asset governance, including product lifecycle, authoritative sources, data contracts, service expectations, certification and health measures.
• Strong knowledge of business, technical and operational metadata, catalogues, marketplaces, glossaries, semantics, critical data elements, lineage and provenance.
• Experience defining data quality rules, thresholds, observability, issue management, evidence, monitoring and remediation.
• Practical technical knowledge of cloud data platforms, lakehouse, data mesh, data fabric, APIs, pipelines, interoperability, master data and reference data; ability to use SQL and an appropriate scripting language, such as Python, to validate metadata, quality rules and supported integrations.
• Hands‑on skills in governance platform configuration, metadata modelling, lineage, data quality rules, certification and workflow automation; ability to assess capability fit, design supported integrations and connect trusted metadata with access approvals, permitted use and lifecycle controls.
• Working knowledge of classification, privacy, security, access, sharing, retention, third party data and governance of data used for analytics and AI.
• Ability to convert approved governance requirements into technical specifications, user stories, metadata schemas, machine‑readable rules, configured workflows and measurable acceptance criteria, maintaining traceability from source requirements to implementation and control evidence.
• Strong knowledge of technology product management practices, including user discovery, roadmap development, backlog prioritisation, agile delivery, release planning and adoption and value measurement; combines product and lifecycle thinking with commercial judgement and structured problem solving to balance value, trust and risk.
• Working knowledge of version control, environment separation, configuration and integration testing, defect management, approved deployment and rollback, least‑privilege access and secure handling of credentials; ability to document solutions and transition scoped capabilities to designated support owners.
• Strong business engagement, facilitation and influencing skills across business, product, data, architecture, engineering and control teams. Able to work with Service Lines, Service Line Quality and the data ecosystem, including the Global Data Office (GDO), Chief Technology Officers (CTOs), Chief Information Officers (CIOs) and Regional Data Stewards; explain technical concepts in business language, clarify needs, negotiate priorities and build agreement on delivery and adoption.
• Applied knowledge of DAMA DMBOK, EDM Council DCAM or CDMC, and relevant data, risk and technology standards.

Supervision Responsibilities:

• Operates with a high degree of independence within approved governance, policy and delivery parameters, with direction on major priorities and material accountability decisions.
• Has no direct reports and no indirect supervisory accountability.
• Provides specialist functional leadership and coordinates work across data, product, business and technology teams; people management accountability remains with the relevant team leaders.

Other Requirements:

• Operates within the Global Data Stewardship Office and aligns product and asset governance to DSO strategy, the Global Data Stewardship Policy and priorities approved through relevant EY governance forums.
• Works globally across the Global Data Stewardship Office and partners with the Global Data Office, Client Technology, Enterprise Technology, Information Security, Global Data Protection, General Counsel’s Office, relevant Risk and Business Administration teams, Service Lines, Service Line Quality, Regions and EY member firms.
• Delivers assigned governance configurations, integrations and validation within approved policy, access, architecture, security and change controls, coordinating specialist support and operational handover. Data Owners and product teams retain accountability for purpose, permitted use, quality and outcomes; designated technology and control owners retain policy, enterprise architecture, security approvals, infrastructure engineering, production change authority and operations unless formally reassigned.

Job Requirements:

Education:

• Bachelor’s degree or equivalent tertiary qualification in information systems, computer science, software or data engineering, data science, or a related technical discipline, or equivalent substantial professional experience in technology implementation. Relevant data governance and information management knowledge is essential; candidates from business or information management disciplines must demonstrate equivalent technical foundations and practical implementation capability.

Experience:

• 8 or more years of relevant experience across data governance, data products, data platforms, data sharing, analytics or AI enablement.
• Demonstrated experience establishing data product or asset governance adopted by business and technology teams in a complex enterprise.
• Experience governing data domains, products, assets, marketplaces, contracts, sharing and reuse across cloud, analytics and AI environments.
• Experience defining implementable requirements for registration, cataloguing, metadata, lineage, quality, certification, access, interoperability, monitoring and retirement.
• Experience resolving ownership, authoritative source, product boundary, data contract, quality and control issues across business and technology teams.
• Hands‑on implementation experience with at least one enterprise data governance platform is essential, including configuring metadata models, ownership and stewardship workflows, certification or quality rules, and implementing and validating supported integrations with cloud data platforms, APIs or automation tools. Candidates must demonstrate practical delivery as well as requirements definition or advisory expertise.
• Practical experience applying data product and asset governance through Microsoft Purview, Databricks Unity Catalog or Microsoft Fabric/OneLake is advantageous. Comparable experience with platforms such as Collibra, Informatica IDMC, Alation or Atlan is also valued. Relevant experience should include translating governance requirements into metadata models, ownership and stewardship workflows, certification criteria, lineage, quality measures or governed access and reuse. Experience with every named platform is not required.
• Demonstrated experience applying technology product management practices to deliver data product or asset governance capabilities from user discovery, roadmap and backlog definition through solution design, hands‑on configuration or integration, testing, approved release, adoption and operational handover.
• Evidence of measurable improvements from technology‑enabled governance, such as increased metadata coverage, faster product onboarding or certification, improved data quality, automated control evidence or greater governed reuse.
• Demonstrated experience partnering with business and technology stakeholders in a global, federated organisation, translating business needs into technical delivery and influencing stakeholders who do not report directly to the role.

Certification Requirements:

• Relevant credentials such as DAM