ICT Senior Data Engineer at GEMS

Job Summary ICT Senior Data Engineer (Azure, Python & R) – a six‑month fixed‑term contract aligned to the operational requirements of the ICT Division. The incumbent reports directly to the Senior Manager: Data Warehouse and Business Intelligence and is based at Head Office – Pretoria. Remuneration: R to R per month, depending on skills and experience. Closing date for applications: Tuesday, 16 December 2025. Duties & Responsibilities Design, build, and optimise data pipelines and architectures that support advanced analytics, machine learning models, and data‑driven decision‑making. Implement robust and scalable data solutions using Microsoft Azure technologies (Azure Data Factory, Synapse Analytics, Databricks, Data Lake Storage). Develop and maintain Python and R scripts for data processing, automation, and statistical analysis. Collaborate closely with data scientists, analysts, and engineering teams to ensure seamless integration of data solutions across systems. Ensure data quality, compliance, and governance through systematic testing and monitoring. Support CI/CD processes for automation of data workflows and adhere to data security best practices. Maintain and support the operational environment to ensure high availability and performance of data systems. Develop training materials, documentation, and best practices for effective use of open‑source tools (Python & R) for corporate use. Facilitate knowledge transfer sessions to enhance analytics and data management capabilities across GEMS. Ensure compliance with organisational policies, POPIA, and relevant data protection regulations. Qualification Requirements A Diploma or University Degree in Computer Science, Information Management, Data Science, or a related field (NQF level 6). Minimum of 8 years’ relevant experience as a Data Engineer or in a similar role. Strong expertise in Microsoft Azure (Data Factory, Synapse Analytics, Databricks, Data Lake Storage Gen2). Proficiency in Python (Numpy, Pandas, Matplotlib, Seaborn) and R for data processing and statistical modelling. Advanced knowledge of SQL, data warehousing, and data modelling principles. Experience with version control (Git, DevOps CI/CD pipelines). Understanding of data governance and security best practices. Added advantage: experience with real‑time data streaming (Kafka, Event Hubs); ML lifecycle tools (MLflow, Azure ML); BI tools (Power BI, Tableau); containerisation (Docker), and orchestration (Kubernetes, Airflow). Skills Strong analytical and problem‑solving skills. Excellent understanding of data engineering and systems integration. Proven experience delivering scalable, efficient, and high‑quality data solutions. Strong knowledge of data processing frameworks and database administration. Excellent communication and documentation skills. Ability to collaborate effectively with cross‑functional teams. Strong project and time management abilities. Behavioural Competencies Integrity – professionalism, fairness, and confidentiality. Innovation – exploring creative and modern data engineering techniques. Excellence orientation – focus on quality, accuracy, and continuous improvement. Collaboration – building constructive relationships with internal and external stakeholders. Member‑centric approach – acting in the best interest of Scheme members and organisational objectives. Analytical thinking – using critical reasoning and data insights to solve challenges. Adaptability – performing effectively in a dynamic and rapidly evolving environment. Communication – clearly conveying technical and analytical concepts to non‑technical audiences. Desirable Understanding of medical scheme operations, healthcare data, or actuarial analysis. Experience working in regulated environments with data compliance and reporting requirements. Employment Information Seniority level: Mid‑Senior level Employment type: Full‑time Job function: Information Technology Industry: Wellness and Fitness Services GEMS employs people with the highest level of integrity – submission to the appropriate pre‑employment assessment is obligatory to be considered for the position. Kindly note that information provided for the application may be shared with a third party for vetting purposes and will be stored by GEMS for a period of 5 years. Information is required for Employment Equity purposes and is used strictly according to the intended purpose of collection, unless there is a legal need or permission is granted by the applicant to use it for another purpose. If you wish to have your information removed from the GEMS database, kindly send a request in writing to (Email Address Removed). GEMS adopts a hybrid work model. GEMS is guided by the principles of employment equity. Preference will be given to groups underrepresented in accordance with GEMS employment equity plan. An employee must be in their current role for 12 months before being considered for other vacancies within the Scheme. GEMS reserves the right not to proceed with an appointment. Successful candidates will be required to seek approval to conduct other work outside of GEMS. Employees are required to conduct themselves in a manner that reflects the organisation's paramount values: Excellence, Member Value, Integrity, Innovation, and Collaboration. #J-18808-Ljbffr