Data Engineer

Data Engineer

Department: [SBSS] Enterprise Data Management

Employment Type: Permanent
- Full Time

Location: Newcastle

Compensation: £53,000 - £67,000 / year

At Somerset Bridge Group, we're transforming our data platform to create a modern, cloud-based data ecosystem that powers smarter decision-making across the business. As part of this journey, we're consolidating our data capabilities onto a single Azure Databricks platform, leveraging technologies including Azure Data Factory, Delta Lake, Unity Catalog and Power BI to unlock new insights and drive innovation.

Joining our Enterprise Data Team
, you'll play a key role in designing, building and optimising scalable data solutions that support Pricing, Underwriting, Claims and wider business operations. Working with large and complex datasets, you'll develop robust data pipelines and platforms that enable analytics, reporting, machine learning and AI-driven initiatives across the organisation.

You'll be responsible for building and maintaining data pipelines using Azure Databricks, Azure Data Factory and Delta Lake, supporting the modernisation of legacy platforms while ensuring data quality, reliability and performance. The role will also involve implementing data governance and security controls, optimising cloud-based data infrastructure, and supporting both real-time and batch data processing.

Working closely with Data Architects, Analysts, Pricing teams and Technology colleagues, you'll help shape the future of SBG's enterprise data platform, delivering scalable, secure and efficient solutions that support strategic business objectives and regulatory requirements.

This is an exciting opportunity to join a growing Enterprise Data Team and make a significant impact on the development of a modern Azure-based data platform, helping to drive data-led innovation across the business.

• Design, build and maintain scalable data pipelines using Azure Databricks, Azure Data Factory and Delta Lake to support both real-time and batch data processing.
• Develop and optimise cloud-based data solutions within Azure, ensuring high performance, scalability and cost efficiency.
• Create robust data models and lakehouse architectures to support analytics, reporting and machine learning initiatives.
• Automate and monitor data workflows using tools such as Databricks Workflows, Delta Live Tables and Azure Monitor.
• Ensure data quality, integrity and governance through effective controls, security standards and regulatory compliance.
• Collaborate with stakeholders across Pricing, Underwriting, Data Science and Technology to deliver data-driven business solutions.
• Implement data security and governance frameworks, including access controls, data lineage and sensitive data protection.
• Drive continuous improvement by adopting new technologies and best practices across the Azure and Databricks ecosystem.

• Strong experience building data pipelines using Azure Data Factory, Databricks and Azure Data Lake.
• Advanced SQL and Python (PySpark) skills for data transformation, automation and optimisation.
• Hands-on experience with Delta Lake, Spark, Databricks Workflows and Structured Streaming.
• Knowledge of data warehousing, lakehouse architectures and dimensional modelling.
• Experience delivering scalable, high-quality data solutions to support analytics, reporting and machine learning.
• Familiarity with real-time data processing, APIs and streaming technologies such as Kafka or Azure Event Hubs.
• Experience with CI/CD, Azure Dev Ops, Git Hub Actions and Infrastructure as Code.
• Strong understanding of data governance, security and access controls, including Unity Catalog and Purview.
• Experience monitoring, optimising and troubleshooting cloud-based data platforms.
• Excellent problem-solving, communication and stakeholder management skills.
• Collaborative approach with the ability to work effectively across technical and business teams.
• Passion for innovation, continuous improvement and emerging data technologies.

• Experience with Scala.
• Exposure to MLOps, feature stores and machine learning platforms.

• Hybrid working - 2 days in the…