Staff BI & Data Engineer

Datatech Analytics; England; Hybrid; GBP 80,000 - 110,000; Full time

Job summary

Datatech Analytics in Berkshire is seeking a Staff BI & Data Engineer to own data pipelines from source to reporting, leveraging Azure Databricks, Unity Catalog and Power BI to deliver reliable insights for commercial and operational decisions.

You will partner with stakeholders to understand needs, improve data quality, implement CI/CD, and mentor teammates while strengthening governance and lakehouse architectures in a hybrid work setting.

Qualifications

• Strong hands-on experience with Azure Databricks, Unity Catalog and Power BI.
• Proficient in PySpark, SQL and Azure data services.
• Experience building reliable data pipelines from source to reporting.
• Ability to explain trade-offs to senior stakeholders.

Responsibilities

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

Skills

Databricks

PySpark

Delta Lake

Unity Catalog

Power BI

DAX

RLS

SQL

Azure data services

Stakeholder communication

Delivery ownership

Problem solving

Tools

Git

CI/CD

Azure Databricks

Job description

Location: Berkshire | Hybrid – Flexible office attendance 1-2 days per month

Ref: J13180

A financial services business is looking for a Staff BI & Data Engineer with strong hands-on experience in Azure Databricks, Unity Catalog and Power BI, and an understanding of how data informs commercial and operational decisions.

You’ll take ownership from source through to reporting, developing reliable pipelines, well-structured data models and Power BI insights that give stakeholders confidence in their decisions.

This role suits someone who investigates problems independently, weighs up the options and takes responsibility for delivering practical solutions. You’ll work closely with stakeholders to understand their needs, maintain accurate and useful reporting, and strengthen engineering practices while supporting colleagues.

What you’ll do

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

What you’ll bring

• 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.
• A track record of independently owning delivery, resolving complex problems and introducing improvements.
• Clear communication and the confidence to constructively challenge requirements and existing approaches.
• Experience of Microsoft Fabric would also be useful.