Middle Data QA Engineer (#4133)

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, we’ve 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 :

• 2+ 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

   

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits