As a Senior Analytics Engineer, you’ll lead curated data modelling within our Lakehouse environment, translating complex business requirements into robust SQL and PySpark transformation pipelines. You’ll take ownership of the data serving layer, ensuring datasets are performant, well‑governed and optimised for consumption across the range of Analytics deliverables.  You will play a key role in ensuring that business requirements for data and associated definitions are translated into that curated data layer.

You’ll also act as a technical mentor within the team, setting standards, reviewing designs and supporting the development of less experienced analysts and engineers.

What you’ll do

• Lead the design and delivery of curated, analytics‑ready dimensional and semantic models
• Own KPI definitions, conformed dimensions and semantic consistency across domains
• Build and maintain complex SQL and PySpark transformation pipelines on Databricks
• Ensure data quality, testing, observability and performance across the curated layer
• Lead modelling design reviews and contribute to architectural decisions
• Partner closely with Data Analysts, Data Architects, Data Engineers, and business stakeholders
• Provide technical leadership, mentorship and guidance to analysts and engineers
• Contribute to CI/CD, testing and governance standards across the Data Platform

What we’re looking for

• Significant experience working as an Analytics Engineer in a modern data platform environment
• Expert‑level SQL skills and strong experience with PySpark
• Deep understanding of dimensional modelling, semantic layers and analytics engineering best practices
• Experience working with Databricks and Lakehouse architecture
• Strong stakeholder management skills with the ability to translate complex concepts clearly to analysts and business SMEs
• A collaborative, proactive mindset with a passion for high‑quality, trusted data
• Experience mentoring or leading other engineers