The Senior SQL Developer will play a critical role in Davies' Business Intelligence function, supporting the design and delivery of analytical datasets, reporting logic, and data structures that power enterprise decision-making.

Requirements

into performant SQL solutions: from engineering large, feature-rich datasets for machine learning models to building the query logic behind operational KPIs. The role requires someone who thrives in a complex data environment spanning multiple acquired systems of record across insurance lines of business. Analytical SQL Development & Feature Engineering Write complex, performant SQL to query, transform, and join data across multiple source systems into analytical datasets, including large-scale feature engineering (100+ features) for fraud detection and machine learning use cases.

Develop and maintain stored procedures, functions, and views that serve as the backbone for Power BI reports, operational dashboards, and executive reporting.

into SQL logic: for example, converting defined KPI specifications into reliable, well-documented query structures that operations teams depend on daily. Reporting & BI Support Partner with Power BI developers and BI analysts to build and optimize the SQL layer underlying dashboards and semantic models. Assist with UAT for new reports and reporting structures, validating data accuracy, edge cases, and performance under production conditions.

Support the build-out of new reporting frameworks, including designing query patterns for net-new KPI sets across business units. Data Integration & Transformation Work with data from multiple acquired systems with differing schemas, naming conventions, and business logic: normalizing and reconciling data to enable cross-system reporting. Build and maintain ETL/ELT processes using SSIS, stored procedures, or other tools to move and transform data between source systems and reporting layers.

Create and maintain data feeds and integrations with both internal platforms and external partners. Performance Optimization & Quality Tune queries, indexes, execution plans, and stored procedures for performance: particularly for large, complex datasets that serve time-sensitive reporting. Implement data quality checks and reconciliation processes to ensure integrity across fragmented source systems.

Profile data to identify anomalies, gaps, and quality issues before they reach downstream consumers. Documentation & Collaboration Write clear technical documentation for all SQL objects, data transformations, and business logic.

, clarify ambiguities, and provide technical feedback on feasibility and approach. Participate in code reviews and contribute to team standards for SQL development. Bachelor's degree in Computer Science, Information Technology, or related field.

5–8 years of professional experience writing complex analytical SQL in a production environment. Strong experience with SQL Server (T-SQL), including stored procedures, functions, CTEs, window functions, and dynamic SQL. Experience working with large, multi-source datasets in an environment with fragmented or heterogeneous systems of record.

Insurance industry experience strongly preferred (claims, policy, billing, or related domains). Experience supporting BI/reporting tools (Power BI preferred) with optimized SQL backends. Advanced T-SQL proficiency: comfortable writing and optimizing queries involving complex joins across 10+ tables, feature engineering logic, and business rule implementation Experience with SSIS or equivalent ETL tooling.

Familiarity with dimensional modelling concepts (star/snowflake schemas, conformed dimensions, slowly changing dimensions).

documents and translate them into