Data Engineer

Analytics Engineer

London Hybrid 3 days in office

Up to 70k

We are working with a well established UK investment management firm that is investing heavily into its modern data and analytics capability.

This is not a traditional data engineering role.

They are looking for an Analytics Engineer to take ownership of their Microsoft Fabric analytics platform and act as the technical standard setter within a growing, code first analytics team.

The function is just over a year old, Spark and PySpark driven, and building properly engineered data foundations rather than relying on legacy BI approaches.

The Role

• Own and govern the Microsoft Fabric analytics platform

• Build and optimise Spark and PySpark data pipelines

• Design and implement dimensional models including star schema

• Review and improve existing data models and notebooks

• Mentor and upskill junior team members

• Act as the internal consultant for new data requirements

• Oversee Git usage, branching strategy and code promotion standards

This role combines hands on engineering with modelling authority and platform ownership. It is ideal for someone who wants more influence and responsibility rather than just delivering tickets.

Tech Environment

• Microsoft Fabric

• Azure Databricks

• Spark and PySpark

• SQL

• Azure ecosystem

• Git and CI CD exposure

What They Are Looking For

• Strong hands on Spark or PySpark experience in production

• Confident designing star schema and dimensional models independently

• Experience in Fabric or Databricks ideally both

• Comfortable reviewing code and giving technical feedback

• Exposure to Azure environments

• Financial services experience helpful but not essential

Why This Role

• Genuine platform ownership

• High visibility within the data function

• Opportunity to shape modelling standards

• Influence architectural decisions

• Work within a regulated environment where data quality matters

Hybrid working with three days in office, particularly during the first six months to support team development and knowledge sharing.

If you are looking for a step up into a role with real ownership and influence within analytics engineering, this is worth a conversation.