Job Title: Data Warehouse Engineer (SQL / Azure)
Location: Central London, 80 Fenchurch Street, 2 days per week
Contract: 6 Months
Key Responsibilities
* Design, build, and optimise SQL-based data warehouse solutions supporting underwriting, claims, actuarial, exposure management, and regulatory reporting.
* Develop robust ETL/ELT pipelines using tools such as SSIS, Azure Data Factory (ADF), and Databricks.
* Implement dimensional modelling (Kimball / star schema) for analytical workloads.
* Integrate data from internal and external London Market sources including Lloyd’s, DXC, TPAs, and brokers.
* Build automated data quality checks, lineage tracking, and controlled data releases.
* Collaborate with Product Owners, Underwriters, Actuaries, BI teams, and IT to translate business requirements into technical specifications.
* Support migration of legacy SQL systems into Azure cloud environments, enabling self-service analytics for Power BI and actuarial platforms.
Candidate Profile
Technical Skills:
* Data warehouse design, dimensional modelling, and star schema expertise.
* Experience with ETL/ELT tools (SSIS, ADF, Databricks).
* Knowledge of Azure cloud data stack (SQL Pool, Synapse, Data Lake, ADF).
* Familiarity with APIs, REST, JSON, and flat-file ingestion.
* Performance tuning and optimisation for large-scale data warehouses.
London Market / Insurance Knowledge:
* Policy, claims, and finance datasets, including Lloyd’s submissions & reporting.
* Understanding of underwriting and actuarial processes.
Soft Skills:
* Excellent communication with technical and non-technical stakeholders.
* Strong problem-solving mindset with attention to detail.
* Experience working in Agile / Scrum environments.
* Previous experience with London Market insurers, MGAs, Lloyd’s syndicates, or brokers.
* Data warehouse dimensional modelling and ETL/ELT development.
* Data Quality Assessment and embedding automated checks with lineage and reconciliation.
* Python or PySpark for data transformation.
* Exposure to BI Tools (Power BI).
* Experience with CI/CD, DevOps, and automated data pipelines.
* Master data management experience and orchestration frameworks (Airflow/ADF).
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