Middle Data QA Engineer

N-iX is looking for a Middle Data QA Engineer to join a project in the e-commerce domain. You will be involved in testing validating and maintaining a new Data Lakehouse solution. This role combines hands-on QA work with a focus on data quality accuracy and reliability.

Our Client is a global full-service e-commerce and subscription billing platform on a mission to simplify software sales everywhere. For nearly two decades weve helped SaaS digital goods and subscription-based businesses grow by managing payments global tax compliance fraud prevention and recurring revenue at scale. Our flexible cloud-based platform combined with consultative services helps clients accelerate growth reach new markets and build long-term customer relationships.

Data is at the core of every decision we make. We are building a next-generation data platform that powers analytics insights and innovation. As part of the team you will collaborate with cross-functional teams (Data and Software Architects Engineering Managers Product Owners and Data/Power BI/QA Engineers) and help ensure the quality and integrity of data pipelines transformations and reports.

Key Responsibilities:

• Test and validate new data engineering features ETL/ELT processes and Power BI reports for data accuracy completeness and business rule alignment.
• Verify data integrity across multiple layers: source systems staging (AWS/Snowflake) and reporting (Power BI).
• Design and execute data quality checks reconciliation scripts and validation routines using SQL and/or scripting (Python preferred).
• Identify discrepancies or anomalies in data early and work with engineering teams to resolve root causes.
• Create and maintain test plans test cases and test data for both functional and non-functional aspects of data products.
• Collaborate with product owners to translate requirements into measurable validation criteria.
• Support root cause analysis and contribute to continuous improvement of data governance and observability.
• Optionally perform exploratory data analysis to detect trends or inconsistencies.

Requirements:

• 3 years of experience in QA.
• Strong SQL (joins filtering aggregations CTEs window functions) for data validation and reconciliation.
• Advanced Excel (pivot tables formulas lookups data comparison).
• Understanding of SDLC/STLC agile processes and QA documentation standards (test cases bug lifecycle).
• Experienced writing clear test cases documenting results and concise bug reports.
• Experience in designing and executing data quality checks reconciliation scripts and validation routines using SQL and/or scripting (Python preferred).
• Analytical mindset and strong attention to detail.
• Ability to work independently within a data-driven environment.
• Intermediate English.

Nice to Have:

• Experience with any BI tool (Power BI Tableau etc.)
• Familiarity with cloud data platforms (AWS Snowflake or similar)
• Exposure to ETL orchestration (Airflow Glue etc.)
• Interest in data quality automation or scripting-based testing
• Prior experience in data QA data analytics or data operations