Data Engineer (London Market)

Job Title: Data Engineer (London Market Insurance) About the Role We are seeking an experienced Data Engineer with strong London Market insurance experience to support a Lloyd’s syndicate in delivering a high-quality, scalable data warehouse and analytics platform. This role focuses on building and maintaining SQL-based data solutions that support underwriting, claims, actuarial, exposure management, and regulatory reporting across the syndicate. You will play a key role in designing robust data models, building ETL/ELT pipelines, and ensuring accurate, well-governed data flows across complex London Market datasets including bordereaux, premiums, claims, and Lloyd’s reporting requirements. Key Responsibilities • Design and develop SQL-based data warehouse solutions (T-SQL) • Build and maintain ETL/ELT pipelines using SSIS, Azure Data Factory, and Databricks • Develop dimensional models (star schema / Kimball approach) for insurance analytics • Work with London Market datasets including bordereaux, claims, premiums, and policy data • Support Lloyd’s regulatory reporting (CMR, QMA/QMB, PMDR, etc.) • Implement data quality checks, reconciliation, and data governance controls • Support integration of data from underwriting, claims, finance, and external market sources • Collaborate with underwriting, actuarial, and claims teams to translate requirements into data solutions • Support migration of legacy systems into Azure-based data platforms (Synapse, Data Lake, ADF) Required Experience • Strong experience in London Market insurance (Lloyd’s syndicate, MGA, insurer, or broker) • Solid SQL and data warehouse development experience • Experience with bordereaux processing and insurance data structures (claims, premiums, policy data) • Experience building ETL/ELT pipelines and dimensional data models • Familiarity with Lloyd’s reporting and regulatory data requirements • Experience working with Azure data services (Synapse, Data Lake, Data Factory) Desirable • Experience with Power BI or other BI tools • Python or PySpark for data processing • Exposure to CI/CD and DevOps (Azure DevOps) • Knowledge of data governance, lineage, and data quality frameworks