Lead Data Governance Global Grade 12

Key Outputs

To establish, embed, and operationalize enterprise-wide data governance, ensuring that data across Azure Fabric, One Lake, Dynamics 365, Snowflake and related platforms is trusted, high-quality, secure, and fit for decision-making. The role owns governance frameworks, policies, and operating models, with a strong emphasis on governing data at source and embedding governance into platforms by design.

• Define and own the enterprise data governance strategy and operating model

• Establish roles and accountability (data owners, stewards, custodians) across business domains

• Embed governance into Azure Fabric, One Lake, Snowflake and data platforms

• Own metadata, lineage, and cataloguing via relevant tool

• Drive data quality improvement at source, particularly within Dynamics 365

• Define governance standards for ERP data (master and transactional)

• Establish and maintain data policies, security, and compliance frameworks

• Lead stakeholder engagement and organizational change to embed governance practices

• Enterprise data governance framework and operating model

• Snowflake, Azure fabric and One Lake governance standards and controls

• Trusted, catalogued, and lineage-enabled data assets

• Improved data quality metrics, particularly in Dynamics 365

• Defined data ownership and stewardship structures

• Governance policies (classification, security, retention, compliance)

• Increased trust, discoverability, and usability of enterprise data

Qualification, Experience and Competencies

Minimum Required Qualification:

• Degree in Information Systems, Data Management, Computer Science, or related field (or equivalent experience)

Minimum Required Experience

• Extensive experience leading enterprise data governance initiatives

• Strong experience with Microsoft data platforms (Snowflake, Purview, One Lake)

• Proven experience governing ERP data (preferably Dynamics 365)

• Frameworks and improving data quality at source

Minimum Required Competencies

• Data governance strategy and execution

• Metadata, lineage, and data cataloguing expertise

• Data quality management and root-cause remediation

• Leadership, influence, and stakeholder engagement

• Change management and communication

• Regulatory, risk, and compliance awareness Attention to detail and quality assurance mindset