Lead Data Engineer

SBG are currently seeking a Lead Data Engineer to drive the design, development and evolution of the data platforms and infrastructure that support underwriting, pricing and risk decision-making across the business. We would also welcome applications from experienced Senior Data Engineers who are ready to take the next step into a leadership role. This is a senior technical position with significant influence across the organisation, responsible for delivering scalable, high-performing data solutions that enable advanced analytics, enhance pricing capabilities and support effective portfolio management within the motor insurance market. Working in close partnership with Underwriting, Pricing, Data Science and Technology teams, the Lead Data Engineer will play a key role in shaping and delivering the organisation's data strategy. The role is responsible for ensuring data platforms are secure, reliable and capable of supporting both current operational needs and future growth ambitions. Combining deep technical expertise with people leadership, the successful candidate will mentor and develop a team of Data Engineers, establish engineering standards and best practices, and drive continuous improvement across the data landscape. They will also lead the design and implementation of modern data architectures, enabling high-quality, accessible and trusted data across the business. As a key member of the data leadership team, the Lead Data Engineer will help strengthen risk modelling capabilities, enhance data governance and regulatory compliance, and unlock greater value from data to support strategic decision-making and continued business growth. What you'll be responsible for: Lead the design, development and continuous improvement of scalable data pipelines, platforms and analytical frameworks that support underwriting models, pricing engines, trading performance and portfolio risk analytics. Architect and oversee the integration of complex, high-volume data sources, including telematics, claims, policy and third-party datasets, into governed, enterprise-wide analytics solutions. Own and manage the pricing data environment within the cloud-based data platform, ensuring optimal performance, reliability, scalability and cost efficiency. Partner closely with Pricing, Underwriting, Actuarial and Data Science teams to deliver innovative, data-driven solutions that enhance risk selection, pricing strategy and commercial outcomes. Champion best practice in data governance, data lineage, security and regulatory compliance, embedding appropriate controls and standards throughout the data ecosystem. Drive continuous improvements in platform performance, operational resilience and engineering efficiency, proactively identifying opportunities to optimise processes and technologies. Provide technical leadership and mentorship to Data Engineers, establishing engineering standards, conducting code reviews and fostering a culture of continuous learning and excellence. Coordinate and prioritise team activities across multiple pricing and data initiatives, ensuring resources are effectively aligned to business priorities and delivery objectives. Lead strategic data initiatives, including platform modernisation, cloud migration activities, tooling evaluations and proof-of-concept projects that strengthen the organisation's analytical capabilities. Oversee the development, maintenance and support of pricing data products within the Enterprise Data Platform, ensuring solutions remain reliable, scalable and aligned to business requirements. Collaborate with key stakeholders across the business to translate complex requirements into practical, scalable data solutions that deliver measurable value. Contribute to the development and execution of the broader data strategy, ensuring data engineering capabilities continue to support business growth, innovation and regulatory obligations. What you'll need: Expert-level proficiency in SQL and Python, with extensive experience developing scalable, production-grade data solutions, data pipelines and automation frameworks within complex data environments. Strong expertise in query optimisation, data processing performance tuning and cost-efficient engineering practices across large-scale and high-volume datasets. Extensive hands-on experience with Databricks and enterprise data warehousing technologies, such as Snowflake, PostgreSQL or similar platforms. Advanced knowledge of data architecture, data modelling and data warehousing principles, including dimensional modelling, medallion architecture design and slowly changing dimensions. Proven ability to design and implement scalable Lakehouse and data warehouse solutions that support operational reporting, advanced analytics and machine learning workloads. Significant experience building and managing data orchestration frameworks using tools such as Azure Data Factory or equivalent technologies, with a focus on reliability, observability, testing and operational excellence. Strong understanding of DevOps and CI/CD practices, including version control, automated testing and deployment pipelines, enabling efficient and secure software delivery. Extensive knowledge of data governance, metadata management, data lineage and regulatory compliance requirements, including GDPR, Solvency II and other relevant frameworks. Experience embedding governance controls, auditability, security and access management into data platform and solution design. Strong understanding of insurance data, particularly within motor underwriting, pricing and claims environments, and the role data plays in supporting risk selection, rating and portfolio performance. Ability to collaborate effectively with Underwriting, Pricing, Actuarial and Data Science teams, translating complex technical concepts into meaningful business outcomes. Excellent stakeholder management, communication and influencing skills, with the ability to build strong relationships across technical and non-technical teams. Demonstrated experience mentoring, coaching and developing engineers, providing technical leadership, architectural guidance and constructive feedback to support individual and team growth. Previous people management experience, including performance management, objective setting, workload planning, resource allocation and career development support. Strategic mindset with a passion for innovation, continuous improvement and emerging technologies, driving enhancements to data platforms, engineering practices and analytical capabilities. Strong problem-solving and decision-making skills, with the ability to balance technical excellence, business priorities and operational requirements in a fast-paced environment. Our Benefits Hybrid working – 2 days in the office and 3 days working from home 25 days annual leave, rising to 27 days over 2 years’ service and 30 days after 5 years’ service. Plus bank holidays! Discretionary annual bonus Pension scheme – 5% employee, 6% employer Flexible working – we will always consider applications for those who require less than the advertised hours Flexi-time Healthcare Cash Plan – claim cashback on a variety of everyday healthcare costs Electric vehicle – salary sacrifice scheme 100’s of exclusive retailer discounts Professional wellbeing, health & fitness app - Wrkit Enhanced parental leave, including time off for IVF appointments Religious bank holidays – if you don’t celebrate Christmas and Easter, you can use these annual leave days on other occasions throughout the year. Life Assurance - 4 times your salary 25% Car Insurance Discount 20% Travel Insurance Discount Cycle to Work Scheme Employee Referral Scheme Community support day