N-iX is looking for a Strong Junior/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 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.
- 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
*not applicable for freelancers