Johannesburg: Client Support Data Engineer

Client Support Data Engineer Play a key role in supporting clients with data-driven solutions in a growing international software company. Remote (South Africa) | R18,000 R25,000 per month depending on experience | 8am5pm SAST About Our Client Our client is an international software development company, creator of Quintessence, a specialist data toolkit widely used by asset management firms in South Africa and now expanding into the UK. Their mission is to transform investment research processes through smarter data integration and modelling. The team is young, dynamic, and passionate about tackling complex data challenges while delivering customised solutions tailored to client needs. The Role: Client Support Data Engineer As a Client Support Data Engineer, you will provide technical and analytical support to ensure client implementations of Quintessence run smoothly and meet SLA requirements. You will work closely with both internal teams and clients, troubleshooting issues, managing data requirements, and building solutions that enhance reliability, efficiency, and usability. This is a client-facing technical role with significant opportunity to grow your expertise in financial data integration and analytics. Key Responsibilities Minimum 2 years of experience in data analysis, modelling, and troubleshooting Configure and implement Quintessence software for client environments Provide 2nd Tier client support, including data enhancements and issue resolution Understand and manage client data requirements within the financial markets Build and maintain end-to-end data service solutions and integrations Develop queries combining multiple data sources while ensuring data integrity Recommend improvements to data reliability, efficiency, and quality Provide structured feedback to development teams on functionality and issues Design user interfaces for data uploads and visualisation About You 2 years of experience working with data in a technical support or engineering role Degree in Statistics, Mathematics, Engineering, Informatics, or related field Strong SQL and Excel skills, plus experience in a programming language such as Python (essential) Exposure to data visualisation tools (Power BI, Tableau, or QlikView) (advantageous) Knowledge of APIs, ETL processes, or data warehousing (advantageous) Background in financial services or asset management (distinct advantage) Client-focused mindset with excellent communication skills Ability to multitask, manage competing priorities, and meet deadlines