Sr. Data Governance Analyst, 6 month contract

Key Responsibilities

• Lead the cataloging and enrichment of priority data domains within the enterprise data catalog platform, ensuring completeness of business descriptions, CDE designations, sensitivity labels, lineage documentation, and data ownership assignments.
• Design, implement, and maintain data quality monitoring frameworks and observability patterns across critical datasets; lead root cause analysis and issue remediation efforts in collaboration with Data Stewards, Data Owners, and engineering teams.
• Oversee and maintain the business glossary, data dictionary, and critical data elements (CDEs), driving alignment between business domain leads and technical teams on authoritative definitions and metric standards.
• Lead cross-functional workstreams to operationalize Data Trust processes including stewardship onboarding, certification reviews, governance policy enforcement, and data access governance.
• Perform advanced data profiling, analysis, and lineage tracing across source and target systems to support certification readiness, compliance requirements, and AI enablement initiatives.
• Develop and maintain Data Trust metrics, scorecards, and reporting dashboards that track catalog coverage, data quality health, certified asset counts, and stewardship adoption.
• Act as a subject matter expert and trusted advisor to Data Owners, Data Stewards, technical teams, and business leaders on data governance expectations, issue prioritization, and data quality remediation strategies.
• Design and document improvements to data governance processes, metadata standards, and data quality frameworks, and present recommendations to the Senior Manager, Data Trust.
• Mentor and support junior Data Governance Analysts, providing coaching on tools, governance techniques, and best practices for metadata management and quality assurance.
• Support the governance of AI-ready data assets by ensuring certified datasets meet quality, lineage, sensitivity, and documentation standards required for consumption by analytics and AI systems.

Required Skills & Experience

• Post-secondary degree in Computer Science, Information Management, Business, Mathematics, or a related discipline.
• 3 – 5 years of experience in data governance, data quality, metadata management, or a closely related analytical discipline.
• Demonstrated experience independently leading data governance or data quality workstreams in a cross-functional, enterprise environment.
• Proficiency in SQL and experience with advanced data profiling, analysis, and lineage documentation across enterprise data assets.
• Hands-on experience with enterprise data catalog platforms, metadata management tools, or data quality monitoring platforms.
• Strong knowledge of data governance frameworks (e.g., DAMA-DMBOK, DCAM) and practical experience applying them across business and technical teams.
• Excellent stakeholder management, communication, and influencing skills; ability to present governance findings and recommendations to both business and technical audiences.
• Experience designing and maintaining governance metrics, data quality scorecards, or asset certification frameworks.

Preferred Experience

• Experience in healthcare, health technology, or a highly regulated industry with data privacy requirements (e.g., HIPAA, PIPEDA).
• Familiarity with cloud-based data platform environments (e.g., Databricks, Unity Catalog, Azure, AWS) and data pipeline or transformation tools (e.g., dbt or equivalent).
• Experience supporting AI or machine learning initiatives in a governance or data enablement capacity, including understanding of AI data quality, lineage, and responsible AI requirements.
• Knowledge of Master Data Management (MDM) principles and data standardization practices.
• Relevant certifications in data management, governance, or cloud platforms (e.g., CDMP, DCAM, or platform-specific credentials).