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Data Governance Manager
Job in
Dallas, Dallas County, Texas, 75215, USA
Listed on 2026-09-16
Listing for:
Tredence Inc.
Full Time
position Listed on 2026-09-16
Job specializations:
-
IT/Tech
Information Security & Data Protection, Data Engineering, Information & Knowledge Management, Data Warehousing
Job Description & How to Apply Below
We are seeking an experienced Data Governance and Data Management Architect to lead the design and implementation of enterprise-wide Data Governance, Data Quality, Master Data Management (MDM), Metadata Management, and Data Modeling initiatives. The ideal candidate will have strong expertise in Microsoft Purview, Alation, SQL, Python, and modern data management frameworks to establish trusted, governed, and business-ready data assets across the organization.
Key Responsibilities Data Governance Strategy & Roadmap- Define and implement enterprise Data Governance strategy, operating model, and roadmap.
- Develop Data Governance Blueprint aligned with business objectives and regulatory requirements.
- Establish data ownership, stewardship, accountability, and governance councils.
- Define governance policies, standards, controls, and data lifecycle management practices.
- Drive adoption of data governance across business and technology teams.
- Design conceptual, logical, and physical data models.
- Develop enterprise data models for analytics, reporting, and operational systems.
- Collaborate with business stakeholders to define data domains and business glossaries.
- Ensure consistency and standardization across enterprise data structures.
- Define Data Quality frameworks, KPIs, and governance controls.
- Establish data profiling, validation, monitoring, and remediation processes.
- Implement proactive data quality dashboards and scorecards.
- Work with business teams to address data quality issues and root-cause analysis.
- Develop MDM strategy, roadmap, and implementation blueprint.
- Define golden record, mastering rules, survivorship rules, and reference data standards.
- Lead Customer, Product, Vendor, and Enterprise MDM initiatives.
- Collaborate with business and technical teams to improve master data consistency.
- Implement data cataloging, lineage, impact analysis, and business glossary processes.
- Drive metadata harvesting and metadata governance initiatives.
- Ensure data discoverability and trust across the enterprise.
- Lead implementation and administration of Microsoft Purview.
- Configure data cataloging, lineage, classification, and governance workflows.
- Integrate Purview with Azure Data Services and enterprise platforms.
- Leverage Alation for data cataloging, stewardship, governance workflows, and self-service analytics.
- Optimize metadata management and business glossary capabilities.
- Support regulatory requirements including GDPR, CCPA, HIPAA, SOX, and industry-specific controls.
- Drive data classification, sensitivity labeling, and privacy controls.
- Conduct governance audits and compliance assessments.
- Build SQL-based data quality checks, profiling, and governance reports.
- Enable governance automation through APIs and workflow orchestration.
- Bachelor's or Master's degree in Computer Science, Information Systems, Data Management, or related field.
- 12+ years of experience in Data Governance, Data Management, Data Architecture, or Data Strategy roles.
- Strong experience developing Data Governance Roadmaps and Blueprints.
- Hands-on implementation experience with Microsoft Purview.
- Experience with Alation Data Catalog.
- Strong expertise in Data Modeling techniques and tools.
- Experience implementing MDM solutions.
- Strong knowledge of Metadata Management frameworks.
- Advanced SQL development and optimization skills.
- Proficiency in Python for data automation and analytics.
- Experience working with Azure Data Platform and cloud ecosystems.
- Data Governance Frameworks
- Data Stewardship
- Data Lifecycle Management
- Master Data Management (MDM)
- Reference Data Management
- Metadata Management
- Data Cataloging
- Business Glossary
- Conceptual, Logical & Physical Data Modeling
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