Data Engineer

Requirements

• Bachelor's degree in Computer Science, Engineering, or equivalent experience, with proven experience in data engineering, analytics engineering, or a similar role.
• Strong experience with Azure Data Factory and modern data integration patterns.
• Advanced Power BI capability including semantic data modelling, DAX, and performance optimisation.
• 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 (e.g. Databricks or Fabric).
• Understanding of DataOps principles, including CI/CD, automated testing, monitoring, and data lifecycle management.
• Experience designing medallion (Bronze/Silver/Gold) architectures, lakehouse patterns, and batch/near-real-time processing.
• Awareness of enterprise data needs, including AI/ML enablement, governance, security, reusable data assets, plus strong problem-solving, collaboration, and continuous learning mindset.
• Candidates must be eligible to work in the country where the position is based. Hexcel (NYSE: HXL) is a global leader in advanced composites technology, a leading producer of carbon fiber, and the world leader in honeycomb manufacturing for the commercial aerospace industry.

Additional Information

With our strong investment in research and development and our culture of continuous improvement, Hexcel is the industry leader in the manufacturing of advance composite materials, including carbon fiber, woven reinforcements, resins, prepregs, honeycombs and additive manufactured parts. We invite you to join the Hexcel team at various manufacturing sites, sales offices and R&D centers around the globe. Become a part of the "strength within." Hexcel is currently seeking a Data Engineer for our Duxford, UK location. The selected individual will be responsible for but not limited to the following obligations: 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-premise 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.

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