Head of Data

Company Description 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.

Job Description REQ-03

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 DataOps, automation, monitoring, and performance optimisation practices across the data environment.
• Deliver technical solutions that support current business needs while enabling future growth and innovation.

2. Data Pipeline Development & Integration

• 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 generative AI technologies and intelligent business assistants.
• Collaborate with business stakeholders, analysts, and technical teams to accelerate AI-driven solutions that improve operational performance and customer outcomes.
• Ensure AI-related data environments meet governance, security, and regulatory requirements.

4. Business Intelligence & Data Enablement

• Deliver data structures, models, and platforms that support enterprise reporting, dashboarding, and self-service analytics.
• Partner with business stakeholders to translate reporting requirements into effective technical solutions.
• Improve access to trusted management information that supports operational and strategic decision-making.
• Enable business users to access reliable data through modern analytics platforms and tools.
• Continuously improve reporting performance, accessibility, and usability.

5. Data Governance, Security & 3rd-Party Compliance

• Implement and maintain enterprise data governance standards, policies, and security controls across all Kaelo systems.
• Conduct stringent security and compliance reviews of all 3rd parties and external vendors accessing, processing, or storing organisational data.
• Ensure robust Data Processing Agreements (DPAs) and Non-Disclosure Agreements (NDAs) are in place, documented, and actively maintained for all 3rd-party engagements.
• Review, document, and formally approve how data is being shared to and from 3rd parties, ensuring all external data flows are continuously monitored.
• Execute periodic reviews and technical audits of internal Kaelo systems and external 3rd-party data handling practices to ensure absolute data security.
• Drive compliance with POPIA, the Cybercrimes Act, applicable FSCA requirements, and internal governance frameworks.
• Establish and enforce data quality, lineage, metadata, retention, and master data management practices.
• Build governance controls directly into data platforms and engineering processes.
• Manage data-related risks and implement corrective actions where required.
• Support internal and external audit activities and ensure timely resolution of findings.

6. Delivery Management & Execution Excellence

• Own the successful delivery of data projects from initiation through implementation and operational handover.
• Develop project plans, milestones, resource requirements, and delivery schedules that align with business priorities.
• Drive delivery against agreed timelines, budgets, and business outcomes.
• Monitor progress, manage dependencies, and proactively resolve obstacles that impact delivery.
• Prioritise work effectively to maximise business value and resource utilisation.
• Ensure solutions achieve defined success criteria and business benefits.
• Provide regular progress reporting and escalation of risks where required.
• Develop and maintain standard operating procedures (SOPs) for the data function, and keep them current as platforms and processes change.
• Operationalise and enforce Kaelo’s data governance, data protection, information security and third-party data-sharing policies across the data function and its vendors, and address non-compliance.
• Maintain a strong focus on execution, accountability, and results.

7. Stakeholder Engagement & Business Partnership

• Build strong relationships with business leaders, technology teams, and external partners.
• Translate complex technical concepts into practical business language that supports informed decision-making.
• Advise stakeholders on data architecture, engineering approaches, analytics opportunities, and emerging technologies.
• Collaborate across departments to accelerate delivery and maximise value realisation.
• Align data engineering initiatives with strategic business objectives and operational priorities.

8. Management, Capability Building & Continuous Improvement

• Provide technical guidance and mentoring to data engineers, analysts, and technical team members.
• Develop internal capability through coachi