Gauteng: Junior Data Engineer posted by Rad Resources

What You’ll Do

• Assist in building, maintaining, and optimising automated data pipelines and workflows.
• Ingest, process, and manage structured, geospatial, satellite, weather, and external datasets.
• Support the development of analytical datasets, dashboards, reporting solutions, and client-facing tools.
• Contribute to internal platforms and data-driven applications used for risk analysis and decision-making.
• Assist with ETL/ELT processes, data transformation, and integration workflows.
• Monitor and improve data quality, integrity, reliability, and performance across systems.
• Collaborate with cross-functional teams on data, analytics, and geospatial initiatives.
• Continuously learn and contribute ideas to improve workflows, automation, and engineering practices.

Requirements

Essential

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, GIS, or a related quantitative field.
• 1–3 years’ experience in Data Engineering, Analytics Engineering, GIS, Data Analytics, or a similar technical role.
• Strong SQL and Python or R skills.
• Exposure to building and maintaining ETL/ELT pipelines and automated workflows.
• Understanding of data modelling principles and reusable analytical datasets.
• Strong analytical thinking and problem-solving abilities.
• Ability to troubleshoot issues, optimise workflows, and work with large datasets.
• A proactive attitude with a strong willingness to learn and grow.
• Good communication skills and ability to work within a collaborative team environment.

Advantageous

• Exposure to GIS, geospatial, satellite, environmental, agricultural, or weather-related datasets.
• Experience with cloud platforms, APIs, or modern data tooling.
• Familiarity with dashboards and data visualisation tools.
• Understanding of risk modelling or analytics environments.

What is on Offer

• Opportunity to join a fast-growing agritech and risk analytics company.
• Hands-on exposure to meaningful, real-world projects and modern technologies.
• A collaborative, close-knit team where your work has visible impact.
• Exposure to agricultural intelligence, risk modelling, and public-sector data ecosystems.
• Career growth and continuous learning opportunities.
• Hybrid working model with flexibility between office and remote work.
• Competitive salary aligned with experience and skills