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Data Governance Specialist
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Data Governance Specialist Join to apply for the Data Governance Specialist role at South African National Blood Service . Key Performance Areas (KPAS) KPA 1: Development, Implementation and Continuous Monitoring of Data Governance Design, document, and roll out data governance policies, standards, and procedures. Ensure frameworks cover data quality, metadata management, data privacy, and compliance. Regularly review and update governance policies to reflect evolving business and regulatory requirements. Manage data governance related projects and initiatives as and when required. Performance Indicators Completion and approval of governance policies within defined timelines. Percentage of data domains covered by governance frameworks. Frequency of policy updates and stakeholder engagement in revisions. Data governance project delivery according to planned outcomes. KPA 2: Data Quality Management Monitor and report on data quality metrics (accuracy, completeness, consistency, timeliness). Identify data quality issues and coordinate with data owners / stewards to resolve them. Facilitate root cause analysis and corrective action plans for recurring data problems. Performance Indicators Improvement in data quality scores over time. Number of data quality issues resolved within SLA. Reduction in business errors linked to data quality. KPA 3: Regulatory Compliance and Risk Management Ensure adherence to relevant regulations (GDPR, POPIA, etc.) and internal compliance policies. Support audits related to data governance and data privacy. Conduct risk assessments and mitigation for data management activities. Liaise and collaborate with the SANBS Compliance function on enterprise-wide compliance interventions. Liaise and collaborate with the SANBS Enterprise Risk Management function on risk management processes and activities. Performance Indicators Number of compliance incidents related to data governance. Audit findings and remediation status. Risk assessments completed and mitigation plans implemented. KPA 4: Stakeholder Engagement and Collaboration Work closely with business units, IT, compliance, and legal teams to ensure data governance alignment. Facilitate data governance councils or committees. Communicate governance policies and their benefits effectively to diverse stakeholders. Performance Indicators Number of stakeholder meetings held and participation rates. Stakeholder satisfaction scores regarding governance support. Level of adherence to governance policies across departments. KPA 5: Metadata and Data Lineage Management Develop, maintain and update centralized metadata repositories, including business glossaries and data lineage for clinical, operational, and research data. Document data lineage to track data origin, transformations, and usage. Ensure accessibility of metadata for users to improve data understanding and trust. Performance Indicators Completeness and accuracy of metadata documentation. Number of data elements with clear lineage documented. User adoption rates of metadata tools and catalogs. KPA 6: Training, Awareness, and Culture Building Develop and deliver training programs on data governance principles, data management and best practices. Promote awareness campaigns to foster a culture of data stewardship and accountability. Measure and improve organizational data governance maturity. Performance Indicators Number of training sessions conducted and attendance. Post-training assessment scores and feedback. Improvements in data governance maturity model scores. KPA 7: Support for Data Stewardship and Ownership Define roles and responsibilities for data owners, stewards, and custodians across clinicaland non-clinical departments. Support data stewards in managing data assets and resolving data issues. Monitor stewardship activities to ensure ongoing compliance. Performance Indicators Number of active data stewards with defined responsibilities. Timeliness and effectiveness of stewardship issue resolution. Compliance with stewardship policies. Minimum Requirements Matric Tertiary qualification in Bachelor’s degree in Information Management, Computer Science, Data Science, Business Administration, or a related field. Preferred/Advantage - Master’s degree or relevant certifications (e.g., DAMA Certified Data Management Professional – CDMP). Advanced Computer Literacy #J-18808-Ljbffr
