Azure Data Engineer

Our client are seeking a Data Engineer to join their UK team and help to deliver an exciting programme of work that began this year. With a D365 programme and the delivery of a Laboratory Information Management System application due to go ahead in the coming months, now is a great time to be joining their team. The Data Engineer will contribute to the design and build of required infrastructure to support optimal extraction, transformation, and load of data from various sources.

Responsible for (but not limited to) the following:

• Design and deliver end‑to‑end data solutions across Azure and Microsoft Fabric platforms.
• Develop and optimise enterprise‑grade Power BI semantic models and reporting solutions.
• Build and maintain scalable, high‑performance data pipelines using Azure Data Factory and Fabric.
• Engineer lakehouse architectures using medallion layers (Bronze, Silver, Gold).
• Design and implement star schemas and analytical data models aligned to business needs.
• Develop and optimise data transformations using PySpark/Spark.
• Integrate data from on‑premises and cloud systems into centralised platforms.
• Create reusable pipelines, datasets, and data components to improve delivery efficiency.
• Ensure data quality, performance, governance, and reliability across all data assets.
• Implement DataOps practices including CI/CD, monitoring, version control, and production support.

Qualifications:

• Bachelor’s degree in computer science, Engineering, or equivalent experience
• Strong experience with Azure Data Factory and modern data integration patterns.
• Advanced Power BI capability
• Strong proficiency in SQL and data modelling for analytics‑ready solutions.
• Experience with Azure cloud data platforms and modern data architectures.
• Knowledge or experience of Microsoft Fabric, including lakehouse/warehouse concepts and Power BI integration.
• Experience with PySpark/Spark‑based data processing
• Understanding of DataOps principles, including CI/CD, automated testing, monitoring, and data lifecycle management.
• Awareness of enterprise data needs, including AI/ML enablement, governance, security, reusable data assets, plus strong problem‑solving, collaboration, and continuous learning mindset.

Location: Cambridge/Hybrid

Candidates must be eligible to work in this country.

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