At a Glance
- Tasks: Lead the design and development of innovative data solutions for underwriting and pricing.
- Company: Join a forward-thinking insurance company with a focus on data-driven decision-making.
- Benefits: Enjoy hybrid working, generous leave, bonuses, and exclusive discounts.
- Other info: Dynamic role with opportunities for growth and innovation in a supportive environment.
- Why this job: Make a real impact in the insurance industry by shaping data strategies and mentoring teams.
- Qualifications: Expertise in SQL, Python, and data engineering with leadership experience.
The predicted salary is between 56700 - 69300 £ per year.
Lead Data Engineer
Department
[SBISL] Data Engineering
Employment Type
Permanent - Full Time
Location
Bristol
Compensation
- Competitive package
- Description
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, Postgre SQL 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 Dev Ops 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
- #J-18808-Ljbffr
Lead Data Engineer employer: Somerset Bridge
Join a forward-thinking company in Bristol that values innovation and employee growth, offering a dynamic work culture where data-driven decisions shape the future. As a Senior Analyst in the Data Enrichment team, you'll enjoy hybrid working, generous annual leave, and a range of benefits including a healthcare cash plan and enhanced parental leave, all while contributing to impactful projects that enhance commercial performance and customer value.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Engineer at Somerset Bridge.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Somerset Bridge.
✨Apply Directly through Our Website
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We think you need these skills to ace Lead Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Somerset Bridge, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Somerset Bridge. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Somerset Bridge
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Somerset Bridge!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
