At a Glance
- Tasks: Ensure data accuracy and integrity through testing and quality assurance processes.
- Company: Dynamic tech company in London with a focus on data excellence.
- Benefits: Competitive pay, flexible office days, and opportunities for professional growth.
- Other info: Collaborative environment with a chance to shape data quality frameworks.
- Why this job: Join a team that values quality and innovation in data management.
- Qualifications: Experience in SQL, data testing, and CI/CD processes required.
The predicted salary is between 30000 - 39000 £ per year.
Role - Data Quality Tester - SQL, data testing, ETL validation, reporting quality assurance, CI/CD testing, and data governance experience. Up to £300 per day.
Location - London Office - up to 2 days a week.
We're looking for a Data Quality Tester to play a critical role in ensuring the accuracy, reliability, and integrity of data across a growing data platform. This position will help accelerate delivery timelines while maintaining high-quality standards across reporting and analytics. This is an excellent opportunity for someone with strong SQL, data testing, ETL validation, reporting quality assurance, CI/CD testing, and data governance experience who enjoys building quality processes from the ground up.
Key Requirements
- Own and enhance data quality frameworks across data ingestion, transformation, and reporting layers.
- Define, implement, and maintain automated data quality rules, determining appropriate failure behaviours based on business impact.
- Develop and maintain automated regression testing for business-critical reports to identify defects before deployment.
- Build contract tests that validate schemas and pipeline outputs, preventing upstream changes from breaking downstream reporting.
- Create and manage representative test datasets covering complex scenarios, including null values, CDC sequences, and multi-entity data.
- Implement automated data assertions and quality gates within CI/CD pipelines to prevent inaccurate or incomplete data reaching production.
- Define and maintain report validation baselines, including row counts, key metrics, and variance thresholds.
- Investigate and reproduce data defects reported by users, converting incidents into reusable automated regression tests.
- Collaborate closely with developers, analysts, and business stakeholders to translate business requirements into measurable and automated data quality controls.
- Review transformation logic, SQL changes, and pull requests to ensure all critical business logic is adequately tested before release.
