Overview
Data Governance Lead Jobs in Centurion, Gauteng, South Africa at Humanatics
Title: Data Governance Lead
Company: Humanatics
Location: Centurion, Gauteng, South Africa
My client in the consulting industry is looking for a Data Governance Lead. The Data Governance Lead is accountable for establishing, embedding, and continuously maturing enterprise data governance framework, operating model, policies, controls, stewardship practices and performance measures required to manage data as a strategic corporate asset across the Company’s operations, technical and corporate data domains.
The role drives improved data quality, accountability, transparency, compliance and decision confidence across the Company’s group of companies.
As the Company increases its use of AI – including generating AI tools, productive models, and analytics automation – this role is also accountable for extending governance disciplines to cover AI specific data risks: training data provenance, model input/output quality, algorithmic transparency, and responsible-AI compliance.
MINIMUM QUALIFICATIONS
Relevant Bachelor’ Degree or equivalent (NQF 7) qualification is essential.
Postgraduate qualification in Data Management, Information Systems, or Business Administration (advantageous).
CDMP (Certified Data Management Professional) – Practitioner or Master level or working towards certification (highly advantageous / preferred).
Exposure to AI governance frameworks or responsible-AI training (e.g., ISO/IEC 42001, NIST AI Risks Management Framework) advantageous.
EXPERIENCE
Experience in the mining industry would be a key advantage.
Minimum 8 – 10 years’ experience in data management, business intelligence, or enterprise data roles.
Minimum 5 years leading governance, data quality, stewardship, master data or enterprise data initiatives in a large enterprise.
Demonstrated experience implementing data governance frameworks in a large, complex organisation – mining, industrial, or heavy-asset environments strongly preferred.
Experience in establishing operating models, governance forums, policies, controls and adoption roadmaps.
Exposure to governing data for AI and big data initiatives – e.g. defining data quality or provenance requirements for a model, participating in AI risk/ethics review, or managing data supply for predictive analytics use case – advantageous.
Proven ability to influence senior stakeholders across business, IT, risk, audit and compliance.
Familiarity with POPIA and other data privacy/regulatory regimes relevant to a JSE/LSE-listing mining company.
KNOWLEDGE AND TECHNICAL SKILLS
Deep working knowledge of DAMA-DMBOK2 knowledge areas: data governance, data quality, metadata management, master data management, data architecture.
Strong understanding of enterprise data architecture and BI ecosystems (SAP BW/4HANA, HANA, BusinessObjects, Tableu, AWS Data Lake).
Working knowledge of data cataloguing/lineage tooling and data quality management platforms.
Understanding of mining value chain data (geology, mine planning, production, processing, metallurgical accounting) advantageous.
Working understanding of AI/ML data lifecycle concepts – training vs. production data, model drift, bias, explainability – sufficient to set governance requirements without needing to build models.
Awareness of emerging AI governance and regulatory frameworks (e.g. ISO/IEC 42001, EU AI Act, NIST AI RMF) and their practical implications for the South African mining group.
Please kindly note that should you not receive feedback within 2 (two) weeks of your application, please consider it as unsuccessful.