Flexible Work Model
Work from home, from the office, or in a hybrid format that supports focus and collaboration.
About the role
In this role, you will lead data quality and testing efforts across large-scale Big Data platforms, ensuring the reliability of data pipelines, processing workflows, analytics, and ML-related solutions. You will work closely with Data Engineering, Data Science, Analytics, and client teams to drive data validation strategies, investigate data issues, mitigate quality risks, and improve the overall quality of the data ecosystem using modern cloud and data technologies.
Responsibilities
- Define test strategies and testing approaches, and coordinate the testing scope across Data Engineering, Data Science, Analytics, and QA
- Identify dependencies, prerequisites, and potential blockers for data test automation solutions
- Manage data quality incidents, communicate findings and risks to clients, and drive issues toward quicker resolution to help unblock the team
- Execute and monitor Airflow DAG runs and validate pipeline results
- Analyze critical datasets and data quality rules, and implement or maintain appropriate checks using Alation or similar tools
- Validate data processing results and key metrics after pipeline execution
- Verify Tableau reports and other Web UI results after data is published
- Support the definition and implementation of regression testing and data validation approaches
- Contribute to improving data quality standards, testing processes, and automation practices
Requirements
- Strong professional experience in Data Testing, with a solid understanding of ETL/ELT and data pipeline testing using Apache Airflow or similar orchestration tools
- Experience testing data-intensive applications and Big Data solutions, AWS experience is preferred
- Advanced SQL skills and strong ability to investigate and validate data using complex queries, Snowflake experience is preferred
- Good Python knowledge and experience creating data validation or automation solutions using Python, Pandas, and/or PySpark
- Experience with data quality and observability tools such as Alation, Soda, or similar solutions
- Strong understanding of data quality dimensions and common data validation techniques
- Experience with regression testing and test automation principles
- Experience investigating, documenting, and resolving data quality incidents
- Understanding of CI/CD and version control practices, such as GitHub Actions or similar tools
- Strong ownership and ability to work independently on complex data quality problems
- Strong communication skills and confidence working with engineering, analytics, and customer teams
SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.
Role Summary
Location
Ukraine
Work type
Remote/Office
Direction
Software Testing
Subdirection
Test Automation
Tech level
Lead
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About us
We are a digital engineering and technology consulting company where expertise grows alongside people. For more than 30 years, we have been elevating technology: helping organizations navigate complex business challenges by combining deep engineering knowledge with thoughtful, research-backed innovation. Our teams work across key areas: digital engineering, data and analytics, Сloud, and AI/ML. In each, we deliver practical, scalable solutions rooted in real business needs and measurable human impact.
You bring your perspective and ambition. We create an environment where your work meets clarity, confidence, and purpose.
We offer
Compensation & Benefits
Competitive, market-based pay, benchmarked by role and location — plus health coverage, paid time off, wellness support, and learning opportunities.
People-first Leadership
Approachable leaders who communicate openly, keep teams close to the strategy, and support long-term planning.
Advanced tech communities
Stay close to AI/ML, Cloud, Quantum Computing, IoT, and Robotics communities, with projects built on modern frameworks.