The Data Governance Analyst supports the execution of enterprise data governance and stewardship activities across data domains. The role works with data owners, subject area stewards, analytics & AI teams, and other stakeholders to operationalize governance tool and processes, define and monitor data quality expectations, resolve data issues, and ensure that business data assets are consistently documented, governed, and ready to support reporting, analytics, and AI-driven use cases.
The role emphasizes stewardship execution, data quality definition and oversight, governance workflows, metadata quality controls, and user enablement to drive consistent adoption of data governance practices across the organization.
This position will offer some flexibility for hybrid work schedules to include both in-office presence and telecommute/virtual work, to be based in either Houston or Dallas, TX.
Key Responsibilities:
Data Stewardship and Governance Execution
• Support data owners and subject area stewards in executing data governance policies, standards, and procedures across assigned data domains.
• Identify, document, and track data issues related to data quality, definitions, usage, lineage, or compliance, and coordinate resolution through established governance processes.
Governance Workflows and Metadata Quality Controls
• Support the design, execution, and continuous improvement of governance workflows for metadata creation, review, approval, and change management.
• Define and apply quality checkpoints to validate metadata content, stewardship inputs, and documentation before assets are published to the data catalog.
• Monitor catalog content for completeness, accuracy, and adherence to governance standards, and coordinate remediation of gaps or inconsistencies.
• Advocate for consistent documentation and stewardship practices to ensure reliable and trusted metadata.
Metadata and Business Glossary Management
• Work with stakeholders to define, document, and maintain business terms, data definitions, and contextual metadata for structured and unstructured data assets.
• Ensure alignment between business definitions, reported metrics, and analytical usage across domains.
• Support effective usage of data governance and catalog tools to maintain high-quality business metadata.
Data Quality Definition, Monitoring, and Issue Management
• Work with stakeholders to define data quality rules, thresholds, and acceptance criteria aligned to reporting, analytics, and operational needs.
• Support monitoring and review of data quality metrics and dashboards to identify trends, risks, and improvement opportunities.
• Analyze data quality issues, assist with root cause identification, and coordinate remediation efforts with appropriate teams.
• Track data quality issues, actions, and outcomes to support transparency and continuous improvement.
Analytics and AI Readiness Support
• Support governance practices that enable analytics and AI use cases by ensuring data is well-defined, documented, governed, and compliant.
• Review metadata usage and data quality trends to help improve data readiness for advanced analytics and AI-driven initiatives.
User Enablement and Adoption
• Create and maintain user guides, job aids, and reference materials for data governance processes, workflows, and tools.
• Support onboarding and ongoing enablement of data stewards and users through training sessions and guidance.
Compliance and Documentation
• Ensure adherence to data governance policies, standards, and procedures.
• Assemble and maintain records, reports, and documentation required to support data governance activities, audits, and reviews.