Data Engineer
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Summary
Intermediate Data Engineer on a one-year fixed-term contract in Cape Town, designing and maintaining ETL/ELT pipelines and scalable data platforms using Python, SQL, Linux and big data technologies, with hands-on work across at least one major cloud (AWS, Azure or GCP) and DevOps-driven automation.
Our client is seeking an Intermediate Data Engineer to join a dynamic technology environment on a one-year fixed-term contract. This role is suited to a data professional with solid experience building and maintaining data pipelines, working with cloud infrastructure and applying strong engineering principles to scalable data solutions.
Key Responsibilities
- Design, develop and maintain reliable ETL/ELT data pipelines.
- Build and support scalable data platforms and engineering solutions.
- Develop data-processing solutions using Python and SQL.
- Work with cloud-based infrastructure across AWS, Microsoft Azure and/or Google Cloud.
- Apply big data technologies to support efficient data processing.
- Work within Linux environments and develop automation scripts.
- Apply DevOps principles to data engineering processes.
- Contribute to automation and continuous improvement of data platforms.
- Troubleshoot technical issues using a systems-thinking approach.
- Ensure solutions are reliable, maintainable and efficient.
- Collaborate with technical teams and stakeholders to deliver data solutions.
Essential Requirements
- Bachelor’s degree in Computer Science, Information Systems or a related field.
- Minimum 3 years’ experience in data engineering, platform engineering or a similar role.
- Strong proficiency in Python and SQL.
- Solid understanding of ETL/ELT pipelines and data engineering principles.
- Proven experience building and maintaining data pipelines and platforms.
- Hands-on experience with at least one major cloud platform: AWS, Microsoft Azure or Google Cloud.
- Practical experience with big data technologies.
- Proficiency in Linux environments and scripting.
- Strong understanding of DevOps principles and automation.
- Excellent problem-solving ability and a systems-thinking approach.
- Strong attention to detail and a reliability-focused mindset.
Advantageous
- Experience with Docker and Kubernetes.
- Exposure to MLOps tools and machine learning workflows.
- Experience implementing CI/CD pipelines.
- Familiarity with real-time data processing systems.
- Experience within healthcare, research or public-sector environments.