Data Quality Lead

Data Quality Governance & Framework

Develop, maintain, and enhance Data Quality Framework, standards, procedures, methodologies, and operating model. Define enterprise data quality principles, controls, KPIs, KRIs, scorecards, and reporting requirements. Ensure alignment with the Data Governance Framework, Data Management Policy, and regulatory expectations, including QCB requirements.

Data Quality Oversight & Monitoring

Define and oversee data quality rules covering accuracy, completeness, consistency, validity, timeliness, uniqueness, and integrity. Establish and monitor data quality performance for Critical Data Elements (CDEs) across business and support functions. Monitor enterprise data quality performance through dashboards, scorecards, and management reporting. Provide regular reporting to Data Governance Committees and senior management on data quality trends, risks, and remediation progress.

Data Issue Management & Escalation

Lead Enterprise Data Quality Issue Management processes, including identification, impact assessment, root cause analysis, remediation tracking, and closure validation. Maintain Enterprise Data Quality Issue management register Challenge and oversee remediation plans developed by Data Owners, Data Stewards, and technology teams. Escalate material data quality risks and unresolved issues through appropriate governance committees for timely resolution.

Regulatory Reporting & Risk Data Quality

Oversee data quality controls supporting regulatory, financial, risk, compliance, and management reporting. Coordinate with Risk, Finance, Compliance, and Business units to improve the quality of data supporting regulatory submissions. Support regulatory examinations, audits, and data-related reviews.

Data & AI Enablement

Ensure that data used in AI, advanced analytics, and machine learning initiatives meets approved quality standards. Collaborate with AI Governance teams to assess data quality risks impacting AI models and AI-enabled business processes. Support the implementation of data quality controls throughout the data and AI lifecycle.

Stakeholder Engagement

Partner with Data Owners, Data Stewards, Business Units, IT, Risk, Compliance, Finance, Operations, and subsidiaries to improve data quality maturity. Promote data quality awareness, accountability, and stewardship across the Group. Facilitate working groups and governance forums focused on data quality improvement initiatives.

Desired Candidate Profile

Qualifications & Experience

• Bachelor's degree in Information Management, Computer Science, Data Analytics, Business Administration, or related field.
• 8-12 years of experience in Data Governance, Data Quality, Data Management, Risk Data Management, Regulatory Reporting, or related domains.
• Experience within banking, financial services, or other highly regulated industries is required.
• Strong knowledge of Data Quality Management, Data Governance, Data Lineage, Metadata Management, Reference Data, and Master Data Management.
• Experience with Data Governance and Data Quality platforms such as Informatica, Collibra, Microsoft Purview, ABACUS, or equivalent solutions.