Data Engineer (Azure Data Factory)

Questions come to you at a microlender in Soweto, and you answer them with data. If you turn up on time and finish what you start, you'll fit in quickly.

You'll be based at a microlender in Soweto. Living nearby, or on a taxi route to it, really helps. Hours are mostly Monday to Friday, with the odd Saturday in busy months.

• Keep a data dictionary so everyone uses the same definitions
• Automate weekly reports that used to take hours in Excel
• Present findings to managers in plain language with clear charts
• Build ETL pipelines in SSIS, Azure Data Factory or Python
• Mask or remove personal information in data sets under POPIA
• Check data quality and trace odd numbers back to the source
• Build simple forecasting and segmentation models in Python or R

• Strong SQL, including joins, window functions and CTEs
• Able to explain what the numbers mean, not just show them
• Careful with sensitive customer data
• Advanced Excel

• Experience with Databricks, Snowflake or Fabric
• Python with pandas for data wrangling
• Industry knowledge in retail, insurance or credit

• Hybrid work with two office days
• Latest laptop with extra screen
• Paid cloud and BI certifications
• Annual bonus tied to company performance

• Build one public portfolio dashboard on a South African open data set if you have no work samples to share.
• Show a before-and-after, like "replaced a 6-hour manual report with an automatic daily dashboard".