Analytics Engineering Lead

Candidate Description

Specialising in data and analytics engineering, this professional brings more than 12 years’ experience shaping gold-layer models, semantic layers and data products that directly drive commercial outcomes. Having built and governed a Major Energy Company's wholesale Databricks lakehouse platform, they confidently translate complex data requirements into dimensional models that underpin decision-making across trading, generation and retail arms.

Adept at Python, SQL, dbt and DAX, they architect robust lakehouse and medallion structures on Azure and Databricks, integrating multi-domain data sources and enabling AI-assisted insights through Databricks Genie and GitHub Copilot. Key accomplishments include delivering a unified national electricity and gas market application, migrating mission-critical demand forecasting models from Excel to Python, and replacing fragmented Tableau estates with a governed Power BI platform — each initiative sharply focused on speed, scalability and stakeholder value.

Beyond technical delivery, they build high-performing analytics teams, embed Git-based workflows and author standards that lift capability company-wide. Their leadership style centres on mentorship, embedded ownership and clear governance, ensuring analytics assets remain trusted and evolvable. With a rare blend of commercial savvy and deep engineering expertise, they consistently deliver data platforms and products that unlock strategic advantage for energy, FMCG, ISV and life-sciences organisations.