Data Analytics Engineer JHB

DVT is a leading technology consulting and software engineering company delivering innovative solutions across Africa and internationally. We partner with clients to solve complex business challenges through software engineering cloud platforms data artificial intelligence and digital transformation. Our teams combine deep technical expertise with a strong consulting mindset to create measurable business value.

Our Data Engineering and Analytics practice is at the heart of this work building governed reusable data products that enable self-service analytics at enterprise scale. We work with cutting-edge cloud platforms including Microsoft Fabric Databricks and Azure Synapse and were proud of our culture of continuous learning internal training and technical excellence.

We are looking for a Data Analytics Engineer to join our team on a high-impact will convert analyst-owned product specifications into governed certified and reusable data products on the Group data platform. You will own the semantic modelling layer that makes shared experiences measurable and comparable across channels and business units.

This is not a bespoke analytics delivery role. You will enable scale through reusable platform capability building data products analytical models and semantic layers that allow Business Unit Analytics teams to self-serve trusted insight using consistent definitions reusable patterns and certified data foundations.

• Design build and maintain governed data products on the Group data platform including bronze silver and gold layers reusable data marts and certified analytical data products.

• Define and maintain semantic models star schemas KPI logic and behavioural entities such as events sessions journeys flows steps intents and transitions.

• Maintain definition consistency across channels and business units.

• Implement validation checks testing frameworks data contracts governance controls and certification evidence so that data product quality is demonstrated rather than assumed.

• Build analytical products and Power BI assets that support descriptive diagnostic predictive and prescriptive analytics over governed data products.

• Create reusable datasets templates onboarding material usage guidance and playbooks so that consuming analytics teams can use the data products without re-engineering the foundations.

• Structure datasets and semantic models so that AI agents conversational analytics and natural language querying return accurate outputs against governed business logic and definitions.

• Use Python SQL Azure DevOps Git and CI/CD practices to automate analytics delivery version control solutions and support performance monitoring and optimisation of owned products.

• 510 years of relevant experience as a Data Engineer and Analyst.

• Experience in Agile methodologies and ways of work.

• Strong experience across data engineering analytics and data modelling ideally in digital channel behavioural platform or financial services environments.

• Experience in enterprise-scale or regulated environments is advantageous.

• Behavioural Analytics technologies experience would be advantageous.

• Strong product mindset with experience of having built or contributed to a framework template library accelerator standards or shared semantic model.

• Strong SQL and Python including data transformation analysis automation and reusable component development.

• Working knowledge of Microsoft Fabric Databricks Delta Spark / PySpark Azure Data Factory Synapse ADLS Gen2 and event or streaming patterns.

• Dimensional modelling and semantic modelling expertise including Kimball star schema design data marts Power BI semantic models and DAX.

• Practical understanding of data governance Microsoft Purview Unity Catalog data contracts data quality testing lineage and certification.

• Azure DevOps Git CI/CD and infrastructure as code exposure.

• Bachelors or Masters in Computer Science / Engineering / Business Analytics.

• Microsoft DP-600 or DP-700 certification preferred; DP-203 PL-300 AZ-900 or relevant Databricks certifications recognised.

• Matric (Grade 12) certificate.

• Bachelors degree in Computer Science Information Technology Engineering or a related field (or equivalent practical experience).

• At least one relevant professional certification (e.g. Microsoft DP-600 DP-700 DP-203 PL-300 AZ-900 or Databricks certifications).