Senior QA Engineer – Data & Analytics

SUMMARY:

We are looking for an experienced QA Engineer – Data & Analytics to join a highly skilled international team working within a complex, large-scale data environment.

This is a hands-on Data QA role focused on ensuring the accuracy, reliability and integrity of data products, pipelines and analytics platforms. You will work closely with Data Engineers, Analysts and Software Engineers to embed quality throughout the data lifecycle, from source systems and transformations through to downstream analytics and reporting.

You will play an important role in defining data quality standards, validating complex data pipelines and migrations, and ensuring that business-critical data remains accurate, consistent and trustworthy.

WHAT WILL YOU BE DOING:

As part of an agile software development team, you will:

• Define and implement data quality and validation strategies across data pipelines, data lakes and warehouses.
• Test data throughout the full lifecycle, validating accuracy, completeness, consistency and integrity.
• Validate ETL/ELT pipelines and data transformations from source systems through to downstream analytics platforms.
• Develop and execute end-to-end data validation and reconciliation tests.
• Use SQL extensively for data validation, reconciliation and investigation.
• Work with engineering teams to implement data contracts, schema validation and anomaly detection.
• Support data quality automation using frameworks such as Great Expectations.
• Perform exploratory data testing and investigate discrepancies across different systems and environments.
• Validate BI and analytics outputs to ensure reports and insights accurately reflect underlying data.
• Support testing of large-scale data migrations, ensuring data integrity and business continuity during cloud transitions.
• Define and monitor data validation criteria, data freshness SLAs and quality metrics.
• Contribute to data observability, lineage, governance and monitoring strategies.
• Identify recurring data quality issues and work with engineering teams to improve processes and prevent future problems.
• Support performance testing across data platforms, including query performance, scalability and reliability.
• Contribute to data security, privacy and compliance testing where required.

WHAT WE ARE LOOKING FOR:

• Strong professional experience in QA within data-focused projects, rather than purely application or UI testing.
• Hands-on experience testing data pipelines, ETL/ELT processes and data transformations.
• Strong SQL skills, with practical experience using SQL for data validation, reconciliation and troubleshooting.
• Good understanding of data engineering workflows and data lake/warehouse architectures.
• Experience testing APIs, integrations and data flows within cloud-based environments such as GCP, AWS or Azure.
• Experience with data quality frameworks such as Great Expectations, or similar.
• Experience validating data across multiple systems and identifying the root cause of discrepancies.
• Understanding of how to validate BI and analytics outputs, using platforms such as ThoughtSpot, Power BI, Looker or Tableau.
• Strong analytical and problem-solving skills with excellent attention to detail.
• Excellent communication skills and the ability to collaborate effectively with Data Engineers, Analysts, Developers and other stakeholders.
• A proactive quality mindset, someone comfortable challenging assumptions and advocating for data quality throughout the development lifecycle.
• Experience working in an Agile, cross-functional team
• Strong verbal and written communication skills in English

NICE TO HAVE:

• Experience testing large-scale cloud or data platform migrations, particularly Databricks-to-GCP environments.
• Experience working with Databricks and/or GCP.
• Understanding of data observability, lineage tracking and monitoring.
• Experience with performance and scalability testing for large data platforms.
• Knowledge of data governance, security and privacy best practices.
• Exposure to machine learning model validation or AI testing.
• Experience working with large-scale or business-critical data environments.

WHAT’S IN IT FOR YOU?

• Be part of our collegial environment where responsibility and authority are shared equally amongst colleagues and help create our company culture.
• A culture in which we don’t criticise failure but ensure we learn from our mistakes
• An Agile environment where your ideas are welcome
• The possibility to grow and experience different projects
• Ongoing Training & Mentoring
• The possibility of travelling