Data Engineer
Summary
Uyandiswa is hiring a Data Engineer in Johannesburg to design, build, and maintain ETL/ELT pipelines, data warehouses, and lakes supporting its Business Intelligence & Analytics practice for clients. Core stack: SQL plus Python/Scala/Java, cloud data platforms (Azure, AWS, GCP, Snowflake, Databricks), with a focus on data quality, governance, and security.
Uyandiswa is seeking a Data Engineer to design, build, and maintain robust data pipelines and infrastructure supporting our Business Intelligence & Analytics practice. You will enable clients to capture, integrate, and process data reliably, laying the foundation for sound analytics and strategic decision-making.
Key Responsibilities
- Design, build, and maintain scalable ETL/ELT data pipelines from diverse source systems.
- Develop and optimise data models, warehouses, and lakes to support reporting and analytics needs.
- Ensure data quality, integrity, and governance across pipelines and storage layers.
- Collaborate with Data Analysts and Business Analysts to understand data requirements and deliver fit-for-purpose datasets.
- Monitor and troubleshoot data pipeline performance, resolving issues proactively.
- Implement data security, access controls, and compliance measures in line with client and industry standards.
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
- Minimum 3-5 years’ experience in a data engineering role.
- Strong proficiency in SQL and at least one programming language (Python, Scala, or Java).
- Experience with ETL tools and cloud data platforms (e.g. Azure, AWS, GCP, Snowflake, Databricks).
- Experience with data warehousing concepts and data modelling techniques.
- Exposure to Financial Services, Energy, Manufacturing, or Consumer Goods data environments advantageous.
Skills and Competencies
- Strong technical problem-solving skills and attention to detail.
- Sound understanding of data architecture, governance, and security principles.
- Ability to translate business and analytical requirements into robust technical solutions.
- Good communication skills for engaging with both technical and business stakeholders.
- Comfortable working in Agile delivery environments.
- Continuous learning mindset, keeping pace with evolving data engineering tools and practices.