Senior Officer, Data Quality

Job Purpose:

Principal Accountabilities:

1. Data Governance Operations

• Execute approved data governance processes and controls in accordance with the Data Management Policy, related standards, procedures and operating model.
• Support the consistent application of data governance requirements across relevant business units and data domains.
• Coordinate with Data Owners, Data Stewards, Technology teams and business stakeholders to collect, validate and maintain governance information.
• Support periodic governance reviews and ensure that required actions, decisions, exceptions and approvals are properly documented.
• Track governance actions and follow up with assigned stakeholders until completion.
• Maintain auditable evidence demonstrating the execution of governance activities and controls.
• Escalate incomplete, overdue or material governance matters through the appropriate channels.

2. Critical Data Elements and Business Glossary

• Maintain the inventory of Critical Data Elements and associated business definitions, ownership, stewardship, source-system mappings and regulatory references.
• Support the identification and assessment of new Critical Data Elements based on regulatory, financial, customer and business-critical requirements.
• Facilitate the review, approval, modification and retirement of Critical Data Elements in accordance with the approved governance workflow.
• Coordinate with Data Stewards and Data Owners to ensure that business definitions are clear, complete and consistently understood.
• Perform completeness and consistency checks on Business Glossary entries.
• Identify missing, duplicate, inconsistent or outdated metadata and coordinate the required updates.
• Ensure that approved changes to definitions, ownership, stewardship, rules or source mappings are reflected in the relevant repositories.
• Retain the required approvals and supporting evidence for changes to Critical Data Elements and glossary information.

3. Data Quality Rule Management

• Support the definition and documentation of data-quality rules for Critical Data Elements.
• Translate approved business data-quality requirements into structured and implementable rule specifications.
• Ensure that data-quality rules include the relevant business logic, technical logic, source-system mapping, threshold and data-quality dimension.
• Support rules covering completeness, validity, consistency and uniqueness, where applicable.
• Coordinate rule validation and approval with Data Stewards and Data Owners.
• Maintain the central repository of approved data-quality rules and related documentation.
• Support the testing of new or modified rules before implementation.
• Ensure that changes to data-quality rules are supported by appropriate approvals and version control.

4. Data Quality Monitoring and Reporting

• Support the execution of periodic data-quality checks against approved rules and thresholds.
• Perform data profiling, validation and analysis to identify data-quality exceptions and recurring patterns.
• Support the preparation and refresh of data-quality dashboards, scorecards and supporting reports.
• Validate data-quality results before distribution to Data Stewards, Data Owners and management stakeholders.
• Prepare summaries of data-quality performance, threshold breaches, trends and priority issues.
• Coordinate with Data Stewards to validate detailed error records and confirm the accuracy of reported exceptions.
• Monitor data-quality results for Critical Data Elements and identify material deterioration or repeated control failures.
• Maintain supporting evidence for data-quality monitoring, dashboard production and reported results.

5. Data Quality Issue Management and Remediation Tracking

• Log identified data-quality issues in the central issue register.
• Ensure that each issue includes a clear description, affected data elements, severity, ownership, target date, status and supporting evidence.
• Coordinate with Data Stewards, Data Owners and Technology teams to support root-cause analysis.
• Track agreed remediation actions and follow up with responsible stakeholders against defined target dates and service levels.
• Maintain a clear and current record of remediation progress, dependencies, decisions and blockers.
• Escalate overdue, repeated or material data-quality issues through the defined governance channels.
• Support the validation of issue resolution and retain evidence before an issue is formally closed.
• Identify recurring issues and contribute to recommendations for sustainable corrective actions and control improvements.

6. Metadata and Data Lineage

• Document and maintain business and technical metadata for Critical Data Elements and other prioritised data assets.
• Support the documentation of source-to-consumption data lineage, including relevant systems, transformations, interfaces and reporting outputs.
• Coordinate lineage validation with Technology teams, Data Stewards and relevant business stakeholders.
• Review and update lineage following material system changes, new data requirements or identified data-quality issues.
• Identify gaps or inconsistencies in lineage documentation and coordinate their remediation.
• Ensure that approved lineage information is stored in the designated governance repository.
• Support the adoption and controlled use of Informatica metadata, glossary, lineage and data-quality capabilities.
• Maintain supporting documentation and evidence for metadata and lineage reviews.

7. Governance Reporting and Data Governance Forum Support

• Prepare data-quality dashboards, governance metrics, status reports and management summaries.
• Support the preparation of materials for the Data Governance Forum and other management or governance meetings.
• Consolidate updates from Data Stewards, Data Owners and Technology stakeholders.
• Maintain meeting packs, decision logs, action trackers, approval records and supporting evidence.
• Track actions arising from governance meetings and follow up with responsible stakeholders.
• Ensure that approved decisions and changes are reflected in the relevant governance repositories and documentation.
• Support the escalation of material data-quality, governance or control matters for management review.

8. Regulatory, Audit and Assurance Support

• Provide documentation, evidence and traceability for regulatory requests, internal audits, external audits and assurance reviews.
• Support the preparation of responses relating to data governance, data quality, Critical Data Elements, lineage and issue remediation.
• Ensure that requested evidence is complete, accurate and maintained in the designated repositories.
• Support the tracking and remediation of findings relating to data governance or data quality.
• Coordinate with relevant stakeholders to obtain responses, documentation and closure evidence.
• Maintain an auditable trail of governance approvals, data-quality monitoring and issue-management activities.

9. Stakeholder Awareness and Support

• Support training, onboarding and awareness activities for Data Owners, Data Stewards and other stakeholders.
• Provide guidance on approved data governance and data-quality processes, templates and responsibilities.
• Assist stakeholders in completing CDE documentation, data-quality rule specifications, issue records and governance submissions.
• Promote consistent data ownership, stewardship, accountability and control practices across the Bank.
• Support the preparation of guidance materials, operating procedures, frequently asked questions and standard templates.
• Encourage timely stakeholder participation in governance reviews, data-quality validation and remediation activities.

10. Continuous Improvement

• Identify opportunities to improve governance processes, control execution, documentation and reporting.
• Contribute to the development and enhancement of data governance and data-quality procedures, templates and operating guidance.
• Support the automation and standardisation of metadata, lineage, data-quality monitoring and issue-tracking activities.
• Recommend improvements based on recurring issues, stakeholder feedback, audit observations and operational experience.
• Monitor relevant data-management practices and contribute to the continuous improvement of the Bank’s Data Management Framework.
• Support the progressive adoption of Informatica and other approved data-management tools

Education and Experience:

• Academic qualification: Bachelor’s degree in Data Management, Computer Science, Information Systems, Business Analytics, Statistics or a related discipline.
• Experience: Minimum 3 years’ relevant experience in data quality, data governance, metadata management, data analysis or a related data-management role, preferably within banking or financial services.
• Practical exposure: Experience in data profiling, data-quality rules and monitoring, issue management, business glossaries, metadata or data lineage, and working with business and technology stakeholders.
• Tools: Hands-on experience with data-governance or data-quality platforms and advanced spreadsheet and reporting skills.