Head of Data

About Kaelo
Kaelo provides essential healthcare solutions ensuring the physical and psychosocial wellbeing of all South Africans towards lasting social change. Kaelo meets the Healthcare needs of Corporate and Retail clients across South Africa – products offerings include Medical Insurance, Medical Aid, Gap Insurance, Kaelo Money and employee assistance programmes.

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Role Purpose

The Head of Data drives the delivery of the organisation’s data strategy through the design, implementation, optimisation, and operational management of modern data platforms, architectures, and engineering solutions.

The role focuses on converting business requirements and strategic objectives into scalable, secure, and commercially effective data solutions that deliver measurable business value. The incumbent takes ownership of end-to-end delivery, ensuring that data engineering initiatives are implemented on time, within budget, and to agreed quality standards.

As a senior technical manager supporting the IT Executive in executing the data strategy, the Head of Data builds and modernises enterprise data capabilities, enables advanced analytics and artificial intelligence initiatives, strengthens data governance and regulatory compliance, and accelerates the organisation’s ability to make data-driven decisions.

Success in this role depends on the ability to balance tactical thinking with hands‑on execution, consistently delivering practical solutions that improve operational performance, enhance decision‑making, reduce risk, and support organisational growth.

Key Responsibilities

1. Data Architecture, Engineering & Platform Delivery

• Design, build, implement, and continuously improve enterprise data architectures that support operational, analytical, and strategic business requirements.
• Deliver scalable cloud‑based data warehouses, data lakes, and lakehouse environments that improve accessibility, performance, and reliability of enterprise data.
• Develop and deploy robust data integration frameworks and ETL/ELT pipelines that support both real‑time and batch processing requirements.
• Lead the migration of legacy data environments into modern cloud‑based architectures while minimising business disruption.
• Optimise data platforms to improve performance, scalability, resilience, and cost efficiency.
• Establish engineering standards, frameworks, and best practices that improve delivery quality and reduce technical debt.
• Drive the adoption of Data Ops, automation, monitoring, and performance optimisation practices across the data environment.
• Deliver technical solutions that support current business needs while enabling future growth and innovation.
• Build, automate, and maintain enterprise data pipelines that ensure reliable and efficient movement of data across the organisation.
• Deliver data integration solutions that consolidate information from multiple internal and external systems into trusted enterprise repositories.
• Implement monitoring, validation, and quality controls that proactively identify and resolve data issues.
• Optimise pipeline performance to improve processing speeds, reduce failures, and minimise operational overhead.
• Eliminate manual data processes through automation and engineering improvements.
• Deliver data solutions that meet defined business requirements, service levels, and operational expectations.

3. Artificial Intelligence & Advanced Analytics Enablement

• Deliver the data architecture and engineering foundations required for artificial intelligence, machine learning, predictive analytics, and intelligent automation initiatives.
• Build scalable data environments that support model development, deployment, monitoring, and continuous improvement.
• Enable secure and compliant adoption of…