Data Product & Asset Governance Associate Director

. Define the governance model for enterprise data products and assets, including ownership, stewardship, decision rights, lifecycle stages and evidence requirements .

Posted 11/12/2026full-timeDallas • Texas • United StatesSenior💰 $150,000 - $297,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data governance, including the establishment of governance models, metadata management, and data quality assurance. Proficient in translating business requirements into technical specifications and managing stakeholder engagement across complex enterprise environments.

Highest-signal resume keywords

Data Governance ExpertiseMetadata ManagementData Quality AssuranceStakeholder EngagementEnterprise Data Governance Platforms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonMetadata ModellingData Quality RulesGovernance Workflow AutomationData Contract ManagementData LineageData ClassificationInteroperabilityCloud Data Platforms

Soft Skills

Business EngagementFacilitation SkillsInfluencing Skills

Tools & Technologies

Microsoft PurviewDatabricks Unity CatalogMicrosoft Fabric/OneLakeCollibraInformatica IDMCAlationAtlan

Certifications & Qualifications

DAMA DMBOKEDM Council DCAMCDMC

Industry Keywords

Data GovernanceData ProductsData PlatformsData SharingAnalyticsAI EnablementData StewardshipData DomainsData QualityRisk Management

Tech Stack

Tools & technologies

CloudInformaticaPythonSQLUnity

About the role

Key responsibilities & impact

Define the governance model for enterprise data products and assets, including ownership, stewardship, decision rights, lifecycle stages and evidence requirements
Establish governance baselines for purpose, authoritative source, metadata, classification, quality, lineage, access, permitted use, retention and monitoring
Create governance pathways based on asset type, risk, use, consumer and platform
Define product entry, certification, publication, service, health, change and retirement criteria
Define data contract responsibilities between producers and consumers
Design, configure and validate registration, onboarding, discovery, access approval, sharing, reuse, certification, change and decommissioning workflows
Conduct stakeholder discovery and translate needs into governance roadmaps, prioritised backlogs, user stories and functional/non-functional requirements
Agree priorities and dependencies with the Global Data Office, CTOs, CIOs, product owners and platform owners
Embed governance checkpoints and measurable acceptance criteria across discovery, design, build, release and operation
Execute configuration and integration testing, coordinate user acceptance testing, resolve defects and prepare release, rollback and support documentation
Evaluate governance platforms and deliver proofs of concept and scoped implementations
Configure metadata models, certification criteria and approved rules; implement supported API, connector or scripting integrations
Translate policy and business requirements into traceable, machine-readable governance rules and metadata
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
Provide specialist functional leadership and coordinate work across data, product, business and technology teams
Deliver assigned governance configurations, integrations and validation within approved controls and coordinate operational handover

Requirements

What you’ll need

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
8 or more years of relevant experience across data governance, data products, data platforms, data sharing, analytics or AI enablement
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 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
Hands-on implementation experience with at least one enterprise data governance platform, including metadata models, ownership and stewardship workflows, certification or quality rules, and supported integrations
Practical experience with Microsoft Purview, Databricks Unity Catalog, Microsoft Fabric/OneLake, Collibra, Informatica IDMC, Alation or Atlan advantageous/valued
Experience applying technology product management practices from discovery through release, adoption and operational handover
Evidence of measurable improvements from technology-enabled governance
Experience partnering with business and technology stakeholders in a global, federated organisation
Deep expertise in modern data governance, federated operating models, data domains, ownership, stewardship and decision rights
Strong knowledge of data product and asset governance, data contracts, certification and health measures
Strong knowledge of 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
Hands-on governance platform configuration, metadata modelling, lineage, data quality rules, certification and workflow automation
Working knowledge of classification, privacy, security, access, sharing, retention, third party data, analytics and AI governance
Ability to convert governance requirements into technical specifications, user stories, metadata schemas, machine-readable rules, workflows and acceptance criteria
Knowledge of technology product management practices, version control, environment separation, configuration and integration testing, defect management, deployment and rollback
Strong business engagement, facilitation and influencing skills
Applied knowledge of DAMA DMBOK, EDM Council DCAM or CDMC, and relevant data, risk and technology standards

Benefits

Comp & perks

Medical and dental coverage
Pension and 401(k) plans
Flexible vacation policy
EY Paid Holidays
Winter/Summer breaks
Personal/Family Care leave
Other leaves of absence
Professional growth
Inclusive culture
Reasonable accommodation for qualified individuals with disabilities