Analytics Engineer

• Transform bronze and silver data in Databricks into clean, tested and documented gold-layer models.
• Design core quote, policy and claims models, with consistent metrics for finance, pricing, marketing and operations.
• Define, document and test shared metrics so teams work from the same numbers.
• Build and maintain a semantic layer, including metric views, Genie spaces and clear data descriptions.
• Investigate incorrect AI-generated answers, improve the underlying models and definitions.
• Provide governed datasets for Power BI reporting and pricing analysis.
• Design data grain and metric history to support forecasting and anomaly detection.
• Apply Git, code review, CI/CD, automated data tests and freshness checks to modelling.
• Set modelling standards and support analysts contributing to shared datasets.

You’ll have worked in analytics engineering, BI engineering or a similar modelling-focused role, ideally with production experience in Databricks or another lakehouse environment. We’re looking for:

• Expert SQL and strong dimensional modelling: facts, dimensions, grain and slowly changing dimensions.
• Hands-on Databricks, including Delta tables, workflows and Unity Catalog.
• Experience with dbt, Databricks Lakeflow or another production modelling framework.
• Git, code review, automated testing and well-maintained documentation.
• Ability to agree metric definitions with commercial stakeholders and explain complex models clearly.

Experience with Databricks metric views, Genie, Power BI modelling, Python, insurance data, pricing models or AI-ready datasets would be beneficial.

• Permanent role with a salary of £65,000 - £90,000.
• Opportunity to establish trusted metrics and modern data modelling standards.
• Work at the intersection of data engineering, BI, commercial analytics and AI.

Interested? Get in touch to find out more.