Work type: Office/Remote Technical Level: Middle Job Category: Quality Control Project: cleverbridge

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)andhelp 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

*not applicable for freelancers