Manager Data Transformation and Platforms

Lead the modernisation implementation and operation of the enterprise data platform to enable digital transformation advanced analytics AI pricing optimisation and data-driven decision-making. Ensure trusted scalable and accessible data capabilities that support business growth and operational excellence.

• Define and execute enterprise data platform strategy and architecture.
• Modernise legacy data environments and establish scalable cloud-based platforms.
• Lead data integration engineering platform delivery and automation initiatives.
• Implement data governance quality privacy metadata and lineage standards.
• Enable trusted enterprise data self-service analytics and AI-driven capabilities.
• Collaborate with business and technology stakeholders to align data initiatives with strategic priorities.
• Manage platform vendors delivery partners budgets and resources.
• Build lead and develop high-performing data and platform teams.

• NQF Level 7 qualification in IT Computer Science Engineering or a related field.
• 5-7 years experience in data engineering data platforms enterprise architecture or related disciplines.
• Experience building or modernising enterprise data platforms.
• Experience with cloud technologies platform engineering and legacy system integration.
• Proven leadership of technical delivery teams.
• Valid drivers licence.

• NQF Level 8 qualification.
• Cloud Data Engineering certifications.
• Architecture certifications (TOGAF Azure AWS GCP).
• Experience in mobility financial services or asset-intensive industries.
• Exposure to AI and advanced analytics initiatives.

• Modernising complex legacy data environments.
• Balancing business priorities with long-term platform transformation.
• Establishing enterprise-wide data governance and ownership.
• Building data engineering capability in a competitive talent market.
• Maintaining operational continuity while delivering transformation initiatives.

• Data platform architecture standards and technology selection.
• Platform investment prioritisation and roadmap sequencing.
• Integration and modernisation approaches for legacy systems.
• Build-versus-buy decisions for data and analytics solutions.
• Resource allocation and platform delivery trade-offs.

Internal: Executives Product Teams IT Data & Analytics Teams
External: Technology Vendors Implementation Partners