Data Engineer

SBG are currently seeking a Data Engineer to support the underwriting function by designing, building and maintaining scalable data solutions that enhance risk assessment, pricing accuracy and operational efficiency across the motor insurance portfolio. The role combines hands-on data engineering expertise with developing leadership capability and strong underwriting domain knowledge, helping to drive the evolution of data and analytics capabilities across the business. Working closely with Underwriting, Pricing, Data Science and Technology teams, the Data Engineer will deliver reliable, high-quality data products that enable data-driven decision making, improve portfolio performance and support strategic business objectives. What you'll be responsible for: Design, develop and maintain scalable data pipelines, platforms and data assets that support underwriting models, pricing capabilities and portfolio risk analytics. Manage and enhance existing production data assets while delivering new data products to meet evolving analytical and business requirements. Drive high standards of data quality, integrity and governance through the implementation of automated validation, cleansing, monitoring and anomaly detection processes. Integrate, transform and harmonise data from a wide range of internal and external sources, including policy, claims, telematics and third-party datasets, to create reliable and analytics-ready data solutions. Develop and maintain data marts, reporting layers and semantic models that provide actionable insights into underwriting performance, loss ratios, portfolio health and key business metrics. Apply data architecture principles, data modelling standards and engineering best practices to ensure solutions are scalable, secure and fit for purpose. Collaborate closely with Underwriting, Pricing and wider business stakeholders to understand data requirements and translate complex business challenges into effective data solutions. Define, monitor and continuously improve key performance metrics to support data-driven decision making and business performance management. Contribute to the development and evolution of the organisation's data engineering capability, promoting consistency, innovation and continuous improvement across the data estate. Mentor and support junior team members, providing guidance, knowledge sharing and code or design reviews to maintain high standards of quality, performance and reliability. Participate in Agile delivery processes, including sprint planning, backlog refinement, estimation and retrospectives, ensuring data engineering priorities are aligned to business and strategic objectives. Work cross-functionally with Data Science, Analytics, Technology and Business teams to deliver robust, scalable and value-driven data solutions that support organisational growth and performance. What you'll need: Strong proficiency in SQL and Python, with the ability to develop robust data solutions, automate processes and support advanced analytical requirements. Experience working with cloud-based data platforms, ideally Microsoft Azure, with exposure to AWS or Google Cloud Platform considered advantageous. Knowledge of data orchestration and workflow management tools, such as Azure Data Factory, to support the efficient movement and transformation of data. Strong understanding of data warehousing concepts, data architecture principles and dimensional data modelling techniques. Experience implementing and supporting CI/CD practices, version control frameworks and collaborative development methodologies, including Git. Proven experience working with Databricks, including data ingestion, transformation and optimisation of large-scale data processing workloads. Understanding of data governance, metadata management and data quality frameworks, including experience with tools such as Great Expectations or similar data validation solutions. Knowledge of Unity Catalog, including data lineage, permissions management, governance controls and data asset tagging. Strong analytical and problem-solving skills, with the ability to translate complex business requirements into scalable data solutions. Understanding of Generalised Linear Models (GLMs) and Gradient Boosting Models (GBMs), including the data and feature requirements associated with insurance pricing models. Knowledge of insurance products, underwriting processes and motor insurance data would be advantageous. Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders. Experience working in Agile delivery environments, collaborating with cross-functional teams to deliver high-quality data products and solutions. Strong attention to detail, commitment to data accuracy and a proactive approach to continuous improvement. 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