Data Analytics Engineer (SQL, Python, Databricks)

Own end-to-end analytics for complex problem spaces, translating ambiguous business needs into structured analyses, KPIs, and actionable insights. You will design scalable data queries and transformations on large, distributed datasets, build data products and executive-ready dashboards, and drive decisions through data storytelling with product, engineering, and business stakeholders. Additional work includes new Capital Data Engineering projects. Roles & Responsibilities: Own end-to-end analytics, translating ambiguous business needs into structured analyses, KPIs, and actionable insights. Design and develop scalable data queries and transformations using SQL, Python, and Databricks on large, distributed datasets. Build and optimise data models to support high-performance analytics and reporting at scale. Develop executive-ready dashboards and data products that enable self-service and decision support. Collaborate cross-functionally to drive decisions through data storytelling. Ensure data quality, governance, and analytics best practices while mentoring junior analysts and elevating team standards. Requirements: Must have: SQL Must have: Python Must have: Big Data Must have: Databricks Good to have: Snowflake Good to have: Machine Learning (ML) Strong data modelling for high-performance analytics and reporting at scale Experience building dashboards and data products for self-service and decision support Strong data storytelling and cross-functional collaboration skills Mandatory for all contractors: maintain 90%+ weekly usage of enterprise-approved AI tools such as GitHub Copilot and Microsoft 365 Copilot Apply AI tools to enhance coding, documentation, data analysis, and decision-making workflows Stay current with evolving AI capabilities to improve delivery quality and velocity