Senior Data Engineer – Channel & Data Insights

Our client is seeking a Senior Data Engineer to join the Channel & Data Insights team of a leading organisation in South Africa.

In this role you will design, build and optimise robust data platforms and pipelines that power critical channel and business insights. Working primarily on the Microsoft Azure data estate (including Microsoft Fabric), you will deliver scalable ETL/ELT solutions, modern data models and reliable data products that enable decision-making across the business.

Key Responsibilities

• Design, develop and maintain scalable data platforms and pipelines using Microsoft Fabric (Lakehouse, Warehouse, Data Pipelines, notebooks, semantic models), Azure Data Factory, Databricks, ADLS Gen2, Azure Synapse Analytics, Event Hubs and Stream Analytics.
  
• Implement robust ETL/ELT processes and modern data modelling approaches (Kimball and/or Data Vault 2.0) to support analytical and operational reporting needs.
  
• Develop and optimize data transformations and processing logic using T-SQL, Python and Apache Spark.
  
• Build and maintain CI/CD pipelines and Infrastructure-as-Code solutions (Bicep, ARM, PowerShell/CLI) via Azure DevOps to ensure reliable, repeatable deployments.
  
• Apply data governance practices using tools such as Databricks Unity Catalog and/or Microsoft Purview to support data quality, lineage, security and compliance.
  
• Collaborate closely with data analysts, product owners and business stakeholders to translate requirements into technical solutions and deliver measurable insights.
  
• Monitor, troubleshoot and continuously improve platform performance, reliability and cost efficiency in an Agile delivery environment.
  
• Contribute to best-practice standards, documentation and knowledge sharing within the data engineering team.
  

Requirements

• 7–8 years of solid hands‑on experience as a platform and data engineer (intermediate to senior level).
• Strong expertise across the Azure data platform, particularly Microsoft Fabric (Lakehouse, Warehouse, Data Pipelines, notebooks, semantic models), Azure Data Factory, Databricks, ADLS Gen2, Azure Synapse Analytics, Event Hubs and Stream Analytics.
• Proven experience in ETL/ELT design, data modelling (Kimball and/or Data Vault 2.0) and data warehousing.
• Strong proficiency in T-SQL, Python and Apache Spark.
• Practical experience with Azure DevOps, CI/CD pipelines and Infrastructure-as-Code (Bicep, ARM, PowerShell/CLI).
• Exposure to data governance tooling such as Databricks Unity Catalog and/or Microsoft Purview.
• Experience working in Agile environments with strong communication and stakeholder engagement skills.
• Advantageous: Relevant Azure certifications (AZ-900 plus one of DP-600 / DP-700 / DP-203) and prior financial services domain experience.