Group IT Data Platform Engineer

Department: Group IT Reports to: Chief Information and Technology Officer (CITO)

About this position

Lanseria, South Africa | Onsite | R800k to R1.2m per annum (experience dependant)

About the Role

We are seeking a Data Platform Engineer to design, build, and optimise our global data platform and analytics infrastructure. This role is central to ensuring our organisation’s data is reliable, secure, and ready to power advanced analytics and AI-driven solutions.

You will lead the data engineering workstream within Group IT, combining hands‑on technical delivery with governance and platform ownership. This is a unique opportunity to bridge technical excellence with business outcomes, contributing to our long‑term digital and data strategy.

Key Responsibilities

• Data Engineering & Platform:
• Design, build, and maintain pipelines and lakehouse workflows using Databricks (Spark, Delta Lake) and Azure Data Factory.
• Model and manage data warehouses and marts for analytics and reporting.
• Administer and optimise relational databases (Azure SQL, PostgreSQL).
• Implement in‑memory caching (e.g., Redis) for low‑latency workloads.
• Document data models, pipelines, and configurations.
• AI, Analytics & Data Products:
• Provide curated datasets and feature pipelines for AI/ML workloads.
• Support integration of AI services into business‑facing data products.
• Ensure analytical workloads are scalable, performant, and cost‑efficient.
• Governance, Security & Compliance:
• Own governance of data platforms and enforce access controls.
• Ensure compliance with cybersecurity and data‑protection standards (POPIA/GDPR).
• Maintain data lineage, cataloguing, and classification.
• Collaborate with Cybersecurity on vulnerability management and audits.
• Coordination & Reporting:
• Act as the data point of contact for Group IT and business stakeholders.
• Deliver monthly operational and governance reports.
• Escalate risks and track remediation progress.
  

Key Performance Indicators

• 99.9%+ availability of data platforms and pipelines.
• SLA compliance for data freshness, accuracy, and incident response.
• 100% adherence to patching, access, and data‑protection standards.
• Continuous improvements in pipeline performance and cost optimisation.
• Audit readiness and complete documentation at all times.
• Stakeholder satisfaction ratings above 90%.
  

Person Specification

Essential

• Bachelor’s degree in Computer Science, Data Engineering, IT, or related field.
• Proven experience designing and operating data platforms in large/multi‑entity organisations.
• Hands‑on expertise with Databricks, Spark, Delta Lake, and Azure Data Factory.
• Strong database engineering skills (Azure SQL, PostgreSQL).
• Experience with data warehouses, marts, and dimensional modelling.
• Working knowledge of AI/ML enablement (feature engineering, vector/embedding stores).
• Understanding of governance, lineage, and data‑protection standards (POPIA/GDPR).

Desirable

• Experience with Redis or equivalent caching solutions.
• Familiarity with Microsoft Fabric, Synapse, Power BI.
• Exposure to MLOps/LLMOps and AI service integration (e.g., Azure OpenAI).
• Infrastructure‑as‑Code (Bicep/Terraform) and CI/CD for pipelines.
• Relevant certifications (Databricks Data Engineer, Microsoft DP‑203/DP‑600/DP‑700).
• Knowledge of Agile or Waterfall methodologies.

Competencies

• Technical competence in complex data platforms.
• Strong focus on data quality and governance.
• Results‑driven with excellent deadline management.
• Adaptability in fast‑changing technical environments.
• Teamwork and collaboration across IT and business functions.