Data Governance Senior Officer

Senior Data Governance Officer

Data Governance Framework And Policies

• Design, maintain, and periodically review the enterprise data governance framework, including data policies, standards, data classification schema, and procedures aligned with industry best practices (e.g., DAMA DMBOK, ISO/IEC 38505).
• Define and drive data ownership and stewardship models, ensuring clear accountability for critical data domains and key data elements across business and technology.

Data Quality, Lineage, and Controls

• Establish and monitor data quality rules, metrics, and key risk indicators (KRIs) for prioritized data sets (e.g., customer, transaction, risk, compliance).
• Oversee implementation of controls for data validation, reconciliation, defect management, and issue remediation, ensuring accurate and complete data for reporting and analytics.
• Promote and support the maintenance of data lineage, metadata, and business glossaries to improve transparency, traceability, and regulatory auditability.

Regulatory Compliance And Risk Management

• Ensure data governance practices support compliance with applicable regulations (e.g., data protection/privacy, AML/CFT, payments and banking regulations), mapping critical data sets to regulatory requirements and reporting.
• Work closely with Risk, Compliance, Information Security, and Legal to embed data controls into risk frameworks and respond to regulatory, supervisory, and audit reviews relating to data.

Committees, Reporting, and Stakeholder Engagement

• Coordinate and, where applicable, chair or act as secretariat to data governance councils, data management committees, and working groups.
• Produce regular dashboards and reports on data quality, issues, risks, and remediation status for senior management, risk committees, and Board-level forums, highlighting key trends and required decisions.

Tooling, Architecture, and Implementation Support

• Support the selection, implementation, and administration of data governance and data quality tools (e.g., data catalog, metadata management, data quality monitoring).
• Collaborate with Data Engineering, Architecture, and IT teams to embed data governance requirements in data platforms, integrations, and analytics solutions.

Awareness, Training, and Culture

• Develop and deliver training, guidance, and communication materials to embed a strong data culture, raising awareness of data responsibilities, privacy, and quality expectations.
• Act as a point of expertise for data governance-related queries and support teams in the application of data governance standards and best practices.

3. Key Relationships

• **Internal Stakeholders:**
• Senior Management, Risk, Compliance, Information Security, Legal, IT/Technology Teams, Data Engineering, Architecture, Data Stewards, and Data Owners.
• **External Stakeholders:**
• Regulatory Authorities, External Auditors, Industry bodies, and Data Governance tool vendors.

4. Qualifications & Experience

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field. Master’s degree or relevant professional certifications (e.g., DAMA, CDMP) is a plus.
• Extensive experience in data governance, data management, and regulatory compliance, preferably in the fintech or financial services sector.
• Strong understanding of data governance frameworks, data management practices, and related technologies.
• Experience with regulatory frameworks (e.g., GDPR, AML/CFT, data protection, payments regulations).
• Experience in the implementation and use of data governance tools (e.g., data cataloging, metadata management, data quality monitoring tools).
• Excellent communication, leadership, and stakeholder management skills.

5. Core Competencies

• Strong analytical and problem-solving skills, with a keen attention to detail.
• Ability to work collaboratively in a cross-functional environment.
• Excellent verbal and written communication skills for effective reporting and training delivery.
• Ability to prioritize tasks and manage multiple projects simultaneously.
• Demonstrates a strong commitment to data protection, compliance, and regulatory standards.
• Expertise in risk management and internal controls.

6. Key Performance Indicators (KPIs)

• Successful implementation and periodic review of data governance framework and policies.
• Achievement of compliance with data governance regulations (e.g., GDPR, AML).
• Maintenance and improvement in data quality metrics, ensuring minimal defects and issues in critical data sets.
• Effectiveness of training programs and stakeholder engagement initiatives.
• Successful integration of data governance practices within new and existing IT solutions and platforms.
• Timely reporting of data governance progress to senior management and board-level committees.