Data Governance Lead

Job Purpose

The role holder is responsible for establishing and institutionalizing the Bank’s enterprise data governance framework, ensuring clear data ownership, stewardship, accountability, and control across all critical systems and data domains. The role holder will define and formalize data ownership structures across business and technology platforms, ensuring that every critical data element has a clearly assigned owner and steward. The role is accountable for governing the creation and use of data reports including departmental reports to ensure alignment with the approved “single source of truth” and prevent fragmented or uncontrolled data usage. This role operates at driving cross-functional alignment, enforcing governance standards, and ensuring that data assets are accurate, controlled, reconciled, and fit for business, financial, and regulatory reporting purposes.

Key Responsibilities

Data Ownership & Accountability Framework

• Establish and maintain a formal Data Ownership and Data Stewardship framework across all key banking systems and data domains.
• Define and document accountability for Critical Data Elements (CDEs), ensuring business owners formally accept responsibility for data accuracy and integrity.
• Ensure ownership structures are embedded within operational processes and governance forums.
• Escalate unresolved data ownership gaps to relevant governance committees.

Data Governance & Compliance

• Support and coordinate the implementation of the bank’s Data Governance framework, guiding teams to consistently apply governance policies across relevant data domains.
• Support regulatory readiness by ensuring data used for reporting aligns with supervisory guidelines.
• Collaborate with different stakeholders to capture and refine data requirements linked to reporting, analytics, and regulatory needs.
• Facilitate workshops to formalize data definitions, data usage boundaries, and Critical Data Element prioritization, ensuring alignment across departments.
• Provide structured analysis bridging business requirements and technical data structures, enabling accurate and consistent data consumption across systems.

Data Modeling & Architecture

• Oversee the development and maintenance of conceptual, logical, and physical data models across assigned banking domains (e.g., retail, corporate, risk, finance, treasury).
• Ensure models adhere to established enterprise data standards, naming conventions, and modeling methodologies.
• Ensure data models support large-scale, high-accuracy financial calculations and reconciliations that align with regulatory, statutory, and internal reporting requirements.

Data Quality, Controls & Assurance

• Define and operationalize Data Quality control frameworks, including profiling, validation rules, exception workflows, and remediation cycles.
• Lead cross‑functional efforts to resolve data issues, including root‑cause analysis, corrective actions, and long‑term data‑quality improvements.
• Maintain oversight of reconciliation processes across financial, operational, and regulatory data pipelines to ensure consistent, trusted data outputs. Support Model Implementation & Delivery.
• Partner with data engineering to ensure models are correctly implemented in databases and reporting systems.
• Participate in system testing, UAT, and validation of data migrations and new product implementations.

Qualifications & Experience

• Bachelor’s degree in in Finance, Data Analytics, Computer Science, Information Systems, or in any other subject or equivalent is required.
• Master’s degree in Finance, Data Analytics, Computer Science, Information Systems, or a related field is preferred.
• Professional qualification in related subjects to Data Analytics, Computer Science, Data Governance is preferred.
• Minimum 3-4 years of practical experience in a bank or same or similar function.