Our client is modernising its entire data landscape and moving a legacy data platform into the Microsoft Azure ecosystem. As part of this transition, a new BI and analytics stack is being built using Microsoft Fabric, Power BI, and a cloud-native architecture.

We’re looking for an experienced Data Engineer who enjoys working with modern tooling, designing clean BI-oriented data models, and delivering reliable data pipelines at scale.

What You’ll Do

• Build and maintain ETL/ELT pipelines in Microsoft Fabric using Dataflows Gen2, PySpark Notebooks, and Pipelines.
• Design BI-ready data models following Kimball principles: star schema, snowflake, SCD, fact tables, dimensions, aggregates.
• Develop high-quality Data Warehouse components that deliver accurate, performant, and auditable data.
• Optimise and monitor data flows, ensuring stability, performance, logging, and traceability.
• Connect to diverse data sources such as Oracle, SQL Server, XML and flat files, and tune extraction logic.
• Automate deployments using Azure DevOps or GitHub Actions and help embed CI/CD practices in the team.
• Apply established technical standards for naming, governance, security, monitoring, and documentation.
• Work closely with data analysts, BI developers, and platform engineers to ensure end-to-end consistency across the ecosystem.
• Document pipelines, transformations and modelling decisions so the platform remains transparent and maintainable.