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A leading financial services company in South Africa is seeking an experienced Senior Data Engineer to design and maintain complex data pipelines and support AWS cloud solutions. The role involves technical leadership, mentoring junior engineers, and collaborating with stakeholders to deliver high-quality data solutions. Ideal candidates will have 4–7 years of data engineering experience and proficiency in Python and SQL.
The Senior Data Engineer is responsible for designing, building, and maintaining robust, scalable data pipelines and platforms to support advanced analytics, BI, and data-driven decision-making.
This individual brings strong technical experience, shows leadership in data initiatives, and works closely with both technical and business stakeholders to ensure high-quality data solutions.
This role bridges implementation and design leadership, playing a critical role in guiding best practices and mentoring junior engineers while contributing hands‑on to complex projects.
A degree or diploma in Computer Science, Information Systems, Engineering, or a related field.
4–7 years of hands‑on data engineering experience.
Advanced proficiency in Python and SQL.
Strong database design knowledge and experience with data warehousing techniques and modelling approaches.
Experience building and maintaining cloud‑based data architecture (AWS preferred).
Design, develop and maintain complex data pipelines from multiple sources into a central data platform / lakehouse.
Ensure reliability, scalability, and maintainability of pipelines.
Optimize data flows and data quality checks.
Contribute to the architectural design and enhancements of the data platform.
Support the implementation of cloud‑first data solutions, primarily in AWS.
Lead initiatives for automation, monitoring, and CI / CD for data engineering workflows.
Provide technical guidance and mentorship to Data Engineers.
Advocate for best practices in data engineering, including version control, testing, and documentation.
Conduct code reviews and support knowledge sharing across the team.
Collaborate with data scientists, analysts, software engineers, and business stakeholders.
Translate business requirements into technical specifications and deliverables.
Support data consumers by developing reports, data products, and self‑service solutions.