Data Governance Lead

Alberta Innovates / InnoTech Alberta • Edmonton, AB

7d • Hybrid

About The Position

As a Data Governance Lead, you will strengthen the organization’s ability to use data as a trusted strategic asset by leading enterprise data governance, data quality, metadata, and lineage practices. The role ensures data is accurate, consistent, well‑defined, and compliant with privacy, security, and regulatory requirements. Working across technical and business teams, the position enables analytics and responsible AI/ML delivery by ensuring high‑quality, well‑governed data and removing barriers that affect model development and deployment. Through program leadership, stakeholder engagement, and continuous improvement, the Data Governance Lead advances organizational data maturity and supports effective decision‑making and innovation.

Requirements

• Diploma in Information Management, Computer Science, Data Management, Information Systems, or a related discipline. Equivalent experience may be considered.
• 7 years of progressively responsible experience in data governance, data management, data quality, metadata management, or related data programs, including experience supporting analytics or AI/ML environments.
• Experience leading multi‑stakeholder data initiatives or programs in complex, multi‑system, or public‑sector/quasi‑government environments.
• Ability to analyze complex data issues, interpret patterns, and recommend practical governance solutions.
• Strong ability to influence without authority across IT, analytics, and business units.
• Effective communication and facilitation skills, with the ability to translate technical concepts for non‑technical audiences.
• Ability to manage multiple priorities, oversee enterprise programs, and deliver results in evolving data environments.
• Proficiency with data governance and metadata platforms and familiarity with AI/ML documentation and lifecycle practices.
• Ability to develop standards, policies, and training materials to support organization‑wide adoption.

Nice To Haves

• Certifications in data governance, data management, or data quality (e.g., DAMA CDMP, DGSP, DCAM) considered an asset.
• Certifications in cloud or data technologies (e.g., Microsoft Purview, Azure Data Fundamentals, Microsoft Fabric) considered asset.
• Certifications related to AI/ML, model governance, or ethical AI (e.g., Azure AI Engineer Associate) considered an asset.
• Knowledge of enterprise data governance frameworks, data lifecycle management, metadata standards, and stewardship practices.
• Understanding of data quality concepts including profiling, measurement, controls, and remediation methods.
• Knowledge of metadata platforms and data catalog tools such as Microsoft Purview and Microsoft Fabric.
• Understanding of AI/ML workflows, model documentation, lineage, and responsible AI practices.
• Awareness of privacy, security, and regulatory requirements for data in public‑sector or quasi‑government environments.

Responsibilities

• Define and maintain governance policies, standards, classification rules, and stewardship models that support consistency, privacy, and regulatory compliance.
• Oversee metadata standards, data definitions, and enterprise glossaries across systems and business units.
• Champion governance practices across the organization through communication, training, and stakeholder engagement.
• Ensure governance alignment with enterprise architecture, information management, cyber/privacy requirements, and AI/ML governance needs.
• Lead and develop the organization’s data quality program, establishing rules, metrics, and controls for critical datasets.
• Oversee data profiling, quality assessments, and root‑cause analysis to identify systemic data issues.
• Collaborate with technical teams and data owners to develop remediation plans that improve accuracy, completeness, consistency, and timeliness.
• Develop and maintain data quality dashboards and reporting mechanisms to support transparency and decision‑making.
• Ensure data quality practices are embedded into ingestion, transformation, and consumption workflows.
• Oversee the enterprise metadata repository, ensuring completeness, accuracy, and alignment with business needs.
• Guide integration of metadata from platforms such as Open Meta Data, Microsoft Purview and Microsoft Fabric.
• Ensure automated lineage practices are implemented for key systems and data products.
• Promote enterprise-wide use of metadata, cataloging, and lineage to support analytics, AI, and operational reporting.
• Monitor evolving best practices in data governance, data quality, AI governance, and information management.
• Identify opportunities to automate governance processes and support scalability.
• Recommend improvements to platforms, processes, and policies to enhance organizational trust in data.
• Support evaluation and acquisition of governance technologies aligned with strategic direction.

Benefits

• Competitive compensation aligned with internal classification and pay bands
• Comprehensive benefits, including health and dental coverage and pension benefits
• Vacation starting at three weeks, plus paid time-off programs that support balance
• Opportunities for learning and professional development
• A respectful, inclusive work environment that values collaboration and diverse perspectives
• Flexible work arrangements, where operationally feasible

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree