Senior Data Tester

We have an urgent requirement for a Senior Data Test Engineer on an initial contract until the end of December. This will be hybrid working with 3 days a week onsite in Central London. The Senior Data Tester will lead and execute data quality and reconciliation testing across Lloyd's of London insurance data flows. The role combines strong manual testing and analytical investigation with semi-automated validation using Azure, Databricks, PySpark, Spark SQL, and scripting. You will validate financial and operational data across ingestion, transformation, and reporting layers, ensuring accuracy of premium, claims, settlements, bordereaux, ledgers, and reconciliation outputs.

• Strong manual testing capability: ability to reason about data, investigate variances, and independently derive expected results.
• Advanced SQL (complex joins, CTEs, window functions, performance-aware querying).
• Hands-on Databricks and Azure ecosystem experience; proficiency in PySpark and Spark SQL for validation.
• Experience with Azure data services and cloud data platforms (e.g., ADLS, Azure Data Factory, Synapse/Databricks patterns).
• Proficiency in scripting/automation (Python preferred) to create repeatable validation checks and accelerate regression testing.
• Understanding of data quality dimensions (completeness, accuracy, consistency, uniqueness, timeliness) and how to test them.
• Strong knowledge of reconciliation methods: record-level matching, tolerance-based comparisons, control totals, and exception handling.
• Ability to document clearly and produce high-quality evidence for governance, audit, or regulatory scrutiny.

Lloyd's Insurance Domain Knowledge Mandatory

• Familiarity with Lloyd's market constructs and insurance data concepts such as syndicates, brokers, coverholders, bordereaux, and premium/claims lifecycle.
• Exposure to currency handling, multi-ledger scenarios, settlement cycles, and financial movement types (paid, outstanding, incurred, reserves).
• Understanding of policy/claim identifiers, endorsements, adjustments, and how they affect reconciliation.

Tools & Technologies

• Azure (ADLS, ADF, Azure DevOps desirable), Databricks, PySpark, Spark SQL, Python, SQL (T-SQL/ANSI), scripting (Shell/PowerShell desirable)
• Test/Work Management: Azure DevOps
• Data formats: Parquet/Delta, CSV, JSON; exposure to Delta Lake concepts beneficial