Credit Risk Data Analyst (Lending)

A retail chain analytics team in George needs dashboards people trust and numbers that add up. It's the kind of job where doing the basics well every day gets you noticed.

You'll report in George. Relocation is not covered for this one. Most weeks are 45 hours, in line with the BCEA.

• Build ETL pipelines in SSIS, Azure Data Factory or Python
• Mask or remove personal information in data sets under POPIA
• Automate weekly reports that used to take hours in Excel
• Meet business users to turn their questions into report requirements
• Keep a data dictionary so everyone uses the same definitions
• Build simple forecasting and segmentation models in Python or R

• Hands-on Power BI, Tableau or a similar tool
• Strong SQL, including joins, window functions and CTEs
• Advanced Excel
• Able to explain what the numbers mean, not just show them
• At least 2 years in a data or reporting role (not needed for graduate posts)
• Careful with sensitive customer data

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

• Hybrid work with two office days
• Latest laptop with extra screen
• Paid cloud and BI certifications

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