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Belonging at Absa

Absa 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.

Job Summary

Job Description

Key Focus Areas

• 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.

Key Accountabilities

• 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.

Operational Effectiveness

• 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.

Good Governance

• 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.

Stakeholder Management

• 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 requirements and control responsibilities.
• Build trusted relationships by being structured, responsive and solution-oriented.

Qualifications and Education

• Relevant diploma or degree .
• Certification in Data Quality, Master Data Management, Data Governance, DAMA, Information Management or Data Analytics would be advantageous.

Field of Study

Preferred fields include:

• Data Management or Data Governance
• Information Management
• Information Systems
• Computer Science
• Data Analytics
• Business Analysis
• Risk Management or Compliance
• Business Administration

Work Experience

• 5 - 8 years’ experience in Data Quality, Master Data Management, Data Governance, Business Analysis, Data Analytics, Reporting or Information Management.
• Experience defining and implementing data quality rules, controls, thresholds and monitoring routines.
• Experience with data quality issue management, root cause analysis and remediation tracking.
• Solid exposure to Customer MDM, customer data, golden source concepts, matching, deduplication or master data controls.
• Experience working with Critical Data Elements and business rules would be advantageous.
• Experience preparing data quality dashboards, governance reports, scorecards or management updates.
• Experience working in a regulated environment, preferably financial services or banking, would be advantageous.
• Experience using tools such as Ataccama, Informatica, Microsoft Purview, SQL, Power BI, Excel, SharePoint or similar platforms would be beneficial.

Competencies

• Strong understanding of Data Quality and Master Data Management principles.
• Good analytical and root cause analysis capability.
• Strong attention to detail and commitment to accuracy.
• Ability to interpret data quality results and translate findings into practical remediation actions.
• Good understanding of controls, governance, evidence and risk management.
• Strong stakeholder engagement and facilitation skills.
• Good written and verbal communication skills.
• Ability to manage multiple priorities and follow through on actions.
• Structured, disciplined and process-oriented approach.
• Comfortable working across business, technology, risk and governance teams.
• Proficient in Microsoft Excel, PowerPoint and SharePoint. Experience with Data Quality, MDM, SQL or reporting tools would be advantageous.

Education