Staff BI & Data Engineer | Databricks

Overview

In this role you own the data journey from source to trusted reporting, enabling customer acquisition, sales and operations decision‑making. You’ll leverage Azure Databricks, Unity Catalog and Power BI to build pipelines, data models and insightful dashboards that stakeholders trust. You will work with senior colleagues to clarify requirements, communicate trade‑offs and drive reliable, governed data solutions. The role emphasizes accountability, practical problem solving, and mentoring peers to raise engineering standards. This is a hands‑on, cross‑functional position with a clear impact on commercial and operational performance.

Pay / Benefits

• hybrid work model
• referral scheme
• gift or voucher scheme

Responsibilities

• Build and optimise data pipelines using Azure Databricks, PySpark, SQL, ADF and ADLS Gen2
• Develop governed lakehouse solutions with Delta Lake, medallion architecture and Unity Catalog
• Own Power BI semantic models, DAX measures and row-level security
• Translate marketing and contact-centre requirements into actionable metrics
• Modernise legacy processes to improve reliability and data quality
• Collaborate with senior stakeholders to clarify requirements and propose solutions
• Strengthen engineering practices through testing, documentation, Git and CI/CD
• Mentor colleagues and share good practice across the team

Key requirements

• Strong production experience with Databricks, PySpark, Delta Lake and Unity Catalog
• Hands-on Power BI expertise including data modelling, DAX, RLS and performance optimisation
• Strong SQL skills and experience with Azure data services
• Experience supporting contact-centre operations and/or performance marketing
• Confidence defining and validating measures such as lead conversion, acquisition costs, attribution, agent performance or service levels
• Track record of independently owning delivery, resolving complex problems and introducing improvements
• Clear communication and ability to challenge requirements constructively
• Experience of Microsoft Fabric would be useful

• Clear communication
• Independent problem-solving
• Mentoring and sharing knowledge
• Azure Databricks
• PySpark
• Delta Lake