(US) 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).