Lead Data Engineer

Lead Data Engineer

London/Hybrid

Circa £95k-£100k + bonus + benefits

Fabric, Azure, Python

Lead Data Engineer with a strong Azure skill set is required by global business. This is a fantastic opportunity to shape the data landscape of a business that's investing heavily in modern data platforms and looking for someone to set the standard.

You'll join a small but highly capable data team that's centralising and unifying data across multiple international divisions with the goal to create a single, coherent view of the business through a shared data ecosystem built on Microsoft Fabric.

Key Responsibilities:

• Lead the effort to define and implement data engineering standards across divisions.
• Collaborate with colleagues in the UK and Europe to unify data models and drive common practices.
• Troubleshoot and optimise pipelines and processes across Fabric, Databricks, and Azure Data Factory.
• Partner with engineers, analysts, and business leaders to ensure that data is consistent, reliable, and ready for advanced analytics.
• Help shape communities of practice and encourage collaboration across international teams.
• Bring strategic thinking to how data supports business decisions, not just technical delivery.

Key Skills:

• Deep experience with Azure, including Python, Spark, Azure Data Factory, Databricks, and related tools.
• Experience with MS Fabric
• A strategic mindset that can translate business needs into scalable technical solutions.
• Strong collaboration skills to work with teams in different countries and cultures; a collegiate, idea-driven approach is key
• A troubleshooting ability to dive into a problem, diagnosing issues, and finding elegant solutions.
• Experience building data models, pipelines, and architectures that can scale across a complex, multi-division organisation.

Why apply?

This is a great opportunity to help define how data is used and governed across an entire business line, with exposure to modern technologies including Microsoft Fabric, Databricks, and cutting-edge data architecture practices