Lead Specialist: Data Quality and Master Data Management

Empowering Africa's tomorrow, together...one story at a time. With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group. Belonging a is committed to creating an inclusive workplace where everyone can thrive.

We are an equal opportunity employer and welcome applications from suitably qualified individuals from diverse backgrounds. In support of our Diversity, Equity, Inclusion and Belonging (DEIB) commitments and Employment Equity objectives, preference may be given to candidates from underrepresented designated groups, including persons with disabilities. We encourage applicants who may require reasonable accommodation during the recruitment process to let us know so that appropriate support can be provided.

• Data quality rule definition and implementation.
• Data quality monitoring and reporting.
• Data quality issue identification, logging and remediation.
• Root cause analysis of recurring data quality failures.
• Customer Master Data Management support.
• Critical Data Element quality improvement.
• Data profiling, validation and exception management.
• Business rule documentation and evidence management.
• Stakeholder engagement with business, technology, risk and data teams.
• Governance reporting on data quality and MDM progress.

• Define, document and maintain Data Quality rules in partnership with Data Owners, Data Stewards, business teams and technology stakeholders.
• Monitor data quality results, trends and exceptions across priority data domains, with a strong focus on customer data.
• Identify, log, track and report data quality issues from detection through to remediation and closure.
• Conduct root cause analysis to identify process, system, control or ownership gaps causing poor data quality.
• Support Customer MDM implementation and adoption, including data validation, matching, survivorship, issue management and business readiness.
• Work with business and technology teams to ensure remediation actions address the underlying cause and not only the symptoms.
• Support the definition and monitoring of Critical Data Elements, including thresholds, rules, controls and ownership.
• Prepare regular Data Quality and MDM reports for governance forums, risk committees and management updates.
• Maintain accurate evidence of Data Quality controls, issue remediation, approvals and decisions.
• Contribute to the implementation of Data Management standards, policies and operating procedures.

• Improve the completeness, accuracy, validity, consistency and timeliness of priority data.
• Ensure data quality issues are tracked clearly, escalated appropriately and resolved within agreed timelines.
• Support the reduction of recurring data defects by addressing root causes at source.
• Strengthen monitoring routines through dashboards, scorecards and exception reporting.
• Drive clear accountability for data quality outcomes across business and system ownership areas.
• Support automation of data quality checks and reporting where possible.
• Ensure Customer MDM activities are aligned to business priorities, risk requirements and operational readiness.

• Promote adherence to Data Quality, Master Data and Data Governance standards.
• Ensure Data Quality rules, thresholds, issues and remediation plans are approved and evidenced.
• Maintain clear audit trails for Data Quality monitoring, root cause analysis and remediation decisions.
• Support governance forums with accurate reporting on data quality performance, risk exposure and MDM progress.
• Escalate material data quality issues, unresolved root causes and ownership gaps through the appropriate governance channels.
• Contribute to improved regulatory reporting, customer data confidence and business decision-making through trusted data.

• Partner with Data Owners, Data Stewards and business teams to define rules, validate issues and agree remediation actions.
• Work closely with Technology, Architecture and MDM teams to resolve system and data integration issues.
• Engage Risk, Compliance, Operations, Finance and Reporting teams to understand downstream impacts of poor data quality.
• Facilitate working sessions to investigate root causes, agree ownership and unblock remediation.
• Provide clear guidance to stakeholders on data quality expectations, evidence…