Senior Data Quality Engineer
Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Oct 20, 2026. GetFrankly scores A on the Alion truth index.
Core details
Company type: International Retail Group - In-house Data & Engineering
Location: Cluj-Napoca, Romania
Work model: Hybrid
Engagement: Employment Contract, Permanent, Full-Time
Role level: Mid level
Experience level: 2-5 Years
Key Skills / Tech Stack: SQL, Python, PySpark, Databricks, data validation, test automation, ETL testing, root cause analysis, Agile
Department: Engineering / Data
Industry: Retail / Tech and digital
About the client
Our client is a large international retail group with an in-house engineering organisation - technology is built internally, not outsourced. Teams own what they design and run, end to end, on platforms that serve the group’s markets and brands across Europe.
The Cluj engineering hub is part of a wider international ecosystem. The culture actively encourages experimentation and new ideas, and the local capability continues to grow.
About the role
As a Data Quality Engineer, you make sure the data flowing through the enterprise data platform can be trusted. You will design the tests and validation routines that check data for accuracy, completeness and consistency, and you will dig into issues until the root cause is found and fixed.
You will sit inside the Data Engineering team and work closely with Data Engineers, Data Designers, Data Quality Analysts and Product Owners. Quality is built into the development lifecycle from sprint planning onwards, not checked at the end.
Responsibilities:
Design, build and maintain automated and manual test scripts and validation routines for data accuracy, completeness and consistency.
Run root cause analysis on quality issues and put solutions in place to prevent them recurring.
Work with Data Engineers, Data Designers and Product Owners to identify quality issues and drive corrective actions.
Take part in agile ceremonies to keep quality visible across the development lifecycle.
Create and maintain quality documentation: test plans, test cases, execution and closure reports.
Support data integration and ETL processes with a focus on reliability.
Keep up with best practices in quality engineering and big data.
Qualifications:
Proven experience as a Quality Engineer, QA Engineer or similar, in a big data environment.
Strong understanding of QA principles, practices and tools.
Proficiency in SQL.
Experience with Python, PySpark and Databricks.
Experience working in agile teams.
Strong analytical and problem-solving skills, with close attention to detail.
Good communication skills and a collaborative approach.
Excellent English, written and spoken.
If you don’t tick every box, apply anyway - the client actively encourages candidates who meet most of the requirements.
About the offer
Our client offers a competitive package and room to grow:
Annual performance bonus and employee referral bonus
Private medical coverage through Regina Maria - Priority Plan, extendable to your spouse or children at no additional cost
Life insurance through Metropolitan Life
Eyeglasses vouchers and a co-funded 7Card fitness membership
Access to LinkedIn Learning, LEO Learning and Bookster
Meal vouchers, plus gift vouchers on several occasions throughout the year
Additional days off when public holidays fall on weekends
Paid leave for special life events
Hybrid working model and a flexible schedule
Modern, collaborative workspace with fresh fruit and premium coffee