Senior Data Tester

CompanyGIOS Technology

LocationLondon Area, United Kingdom

Posted At3/12/2026

UK Visa Sponsorship Analytics

Analytics are greyed out due to low classification confidence (29.0%).

Occupation Type

Electricians and electrical fitters

Occupation Code Skill LevelMedium Skilled

Sponsorship Salary Threshold

£41,700 (£21.38 per hour)

Standard minimum applies

Above analytics are generated algorithmically based on job titles and may not always be the same as the company's job classification. You can also check detailed occupation eligibility, and salary criteria on our UK Visa Eligible Occupations & Salary Thresholds page.

Disclaimer: Hunt UK Visa Sponsors aggregates job listings from publicly available sources, such as search engines, to assist with your job hunting. We do not claim affiliation with GIOS Technology. For the most up-to-date job details, please visit the official website by clicking "Apply Now."

Description

We are looking for Senior Data Tester at London, UK– 3 days per week Onsite

Job Description:

We are seeking an experienced Senior Data Tester, to 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.

Key Responsibilities

Own end-to-end data testing for financial reconciliation pipelines across Lloyd’s insurance datasets (premium/claims/ledger movements).
Perform manual and exploratory data testing: deep dive investigations, anomaly detection, root cause analysis and triage.
Design and execute reconciliation test strategies (control totals, balancing checks, completeness, accuracy, timeliness, and lineage).
Validate ETL/ELT transformations in Databricks using PySpark + Spark SQL; verify joins, aggregations, currency conversions, and business rules.

Build and maintain semi-automated test assets: reusable SQL/PySpark validation scripts, data comparison utilities, parameterized checks, and regression packs.

Develop test cases and test evidence aligned to audit/compliance expectations (traceability from requirements ? test ? results).

Work with Product Owners, Data Engineers, SMEs, and Finance teams to refine requirements and clarify reconciliation logic.

Create defect reports with strong diagnostics (source/target samples, query outputs, record counts, deltas, suspected causes).

Validate data across layers (Raw/Bronze ? Cleansed/Silver ? Curated/Gold) and downstream outputs (reports, extracts, APIs).

Ensure test coverage for edge cases: late arriving data, duplicates, reversals, adjustments, cancellations, and back-dated movements.

Reconciliation checks catch issues early and reduce downstream defects.

Develop reusable scalable, regression packs and reduce manual effort over time.

Clear evidence and reporting that supports audit/compliance expectations.

Faster root-cause resolution through strong diagnostics and collaboration.

Required Skills & Experience

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

Working Style & Soft Skills

Highly analytical, detail-oriented, and comfortable challenging data assumptions.
Strong stakeholder communication—can explain variances and complex reconciliation issues to technical and non-technical audiences.
Comfortable working in Agile teams, delivering at pace while maintaining high quality and traceability.