Data Engineer (Hybrid, Cape Town)

About the role

The Data Engineer will lead the technical implementation of data transformation initiatives, building robust pipelines and AI/ML‑ready data structures. Working in a hybrid setting in Cape Town, you will collaborate across functions to turn strategic direction into production‑grade data capabilities.

Key responsibilities

• Design, build and maintain end‑to‑end automated data pipelines from internal and external sources.
• Platform maintenance and development including calculation development, on‑boarding assets and equipment and continuous improvement.
• Develop, implement and extend the integrated SSOT database, consolidating data from CAMs, ERP, OT/IoT, SharePoint and other platforms.
• Develop modular and scalable data ingestion using API integrations, SQL Stored Procedures and ETL frameworks, maintaining reliable, automated data ingestion between internal and external platforms to the SSOT database.
• Support and provide data development solutions; act as a practical driver and enforcer of the Data Transformation.
• Design and develop scalable data models (staging, core, marts, feature sets) that support strategic reporting, advanced analytics and ML.
• Develop and support workflow automation and lightweight data applications using Power Apps and Power Automate, integrating these solutions with the core data platform.
• Develop ML algorithms for anomaly detection, prediction and neural networks.
• Ensure all data models, pipelines and storage approaches are AI/ML‑ready, including feature‑ready datasets.
• Own end‑to‑end development and processing (data algorithms and ML solutions) including technical platform development, data orchestration and data management.
• Adhere to data governance, security and audit standards; maintain comprehensive technical documentation and change‑management records.
• Work with divisional data owners to reduce data silos, standardise data flows and ensure adherence to agreed standards and timelines.

Required profile

• Full‑stack data engineering competence.
• Ability to translate strategic direction into concrete technical solutions.
• Experience delivering scalable, production‑grade data capabilities.

Required skills

• API integration (REST/JSON, authentication, pagination, error handling).
• ETL/ELT orchestration and job scheduling.
• SQL Stored Procedures.
• Data modeling (staging, core, marts, feature sets).
• Power Apps and Power Automate.
• Machine Learning algorithm development (anomaly detection, prediction, neural networks).
• Data pipeline development and automation.
• SSOT (single source of truth) database integration.
• Data governance and security compliance.