Data Engineer

Who We Are

Since its inception, [Employer hidden — sign up to reveal] Group has sought a different approach to insurance. We are on a mission to be the ‘most inspiring specialty (re)insurance group in the world’. At the heart of [Employer hidden — sign up to reveal] are our people. Working together in dynamic, service-focused teams, we prioritise our customers in everything we do. Collaboration fuels our success, courage drives our innovation and continuous improvement keeps us ahead in a rapidly evolving industry. Our shared commitment is to revolutionise insurance for the better, one day at a time. We also believe that investing in our people is investing in our future. By empowering people across the Group to develop their careers, advance within the Group, and embrace new challenges, we build an environment where growth and learning never stop. Our competitive benefits package, offered via a flexible benefits platform, reflects this. Beyond core benefits, employees have the freedom to tailor their benefits to meet their individual needs, supporting their unique goals and ambitions.

Role Summary

You will work in various settings to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret. Your ultimate goal is to make data accessible so that [Employer hidden — sign up to reveal] stakeholders can use it to evaluate and optimise their performance.

Role Accountabilities

• Develop, create and maintain reliable data pipelines and schemas, applying business logic to transform data from disparate sources into high-quality, governed datasets.
• Design and implement custom ETL/ELT processes, including data marts and schemas, integrating data from versatile sources with data quality measures applied throughout.
• Access, validate and query data from various repositories; build and maintain integration processes using SQL, ETL/ELT tools and scripting languages to support the data warehouse, MI and financial data needs.
• Monitor pipeline performance and apply optimisation techniques including partitioning, indexing and denormalisation; respond to errors and alerts to correct and re-process data as needed.
• Leverage Agile, CI/CD and DevOps methodologies to deliver robust, maintainable data solutions on time and to a high standard.
• Experience designing and developing APIs to support insurance data flows, enabling secure and scalable access to policy, claims, underwriting, and exposure data across internal systems, data platforms, and third‑party providers.
• Strong understanding of Data Mesh within insurance environments, including domain-aligned data ownership across underwriting, claims, pricing, exposure management and finance, treating data as a product to support regulatory actuarial and analytics use cases.

Role Requirements

• Bachelor’s degree or equivalent in an engineering/numerate subject (e.g. Engineering, Stats, Maths, Computer Sciences).
• 5+ years' experience with at least two years working within the insurance industry (e.g. broking, MGA, carrier, or Lloyd's market), with an understanding of insurance data domains such as policy, claims, or bordereaux.
• Hands-on experience with Microsoft Fabric (Lakehouses, Pipelines, Notebooks) or Azure Synapse and related cloud-based data services.
• Experience with Azure Data Factory, Azure Functions, and Azure Service Bus for data integration.
• Proficiency in Python and/or PySpark for pipeline development.
• Knowledge of Data Modelling, Data Warehouse concepts, and project lifecycle best practices.
• Experience with Azure SQL Database, NoSQL solutions (Cosmos DB, MongoDB).
• Familiarity with ETL/ELT patterns, RESTful APIs, and integration testing.
• Experience with Agile and DevOps methodologies.

Skills and Abilities

• Strong logical and analytical mindset, with a structured approach to problem decomposition, root cause analysis, and translating complex business requirements into technical solutions.
• Demonstrable ability to develop complex SQL queries and stored procedures for data transformation and performance optimisation.
• Effective communicator with the ability to build relationships across technical and non-technical stakeholders, including data scientists, analysts, and business teams.
• Self-motivated and delivery-focused, comfortable working in a fast-paced environment managing multiple priorities.
• Attention to detail and a strong sense of data quality and accuracy, particularly when working with financial or insurance datasets.

Additional Information

We are an equal opportunity employer, and we are proud to share that 93% of our employees say they can be themselves at work. We aim to hire our industry's finest people because the best people drive the best outcomes. And we forever challenge the status quo because we know there are always ways to improve things. Because together, we're limitless. We value applicants from all backgrounds and foster a culture of inclusivity. We understand the need for flexibility, so work in a hybrid model. Please let us know if you require any reasonable adjustments during the recruitment process.

FCA Conduct Rules

• You must act with integrity.
• You must act with due skill, care and diligence.
• You must be open and cooperative with the FCA, the PRA and other regulators.
• You must pay due regard to the interests of customers and treat them fairly.
• You must observe proper standards of market conduct.
• You must act to deliver good outcomes for retail customers.