AI Summary
We are looking for a Senior Automation QA Engineer with experience in testing Big Data or data platform projects. The goal is to modernize and scale an enterprise data platform by migrating to a cloud-based architecture. The ideal candidate will have a strong background in functional testing, code validation, and data verification.
Key Highlights
Conduct functional testing and code validation
Develop and maintain automated tests and integration scripts in Python
Collaborate with Data Engineers to troubleshoot issues and maintain high data quality standards
Technical Skills Required
Benefits & Perks
Competitive salary
Flexible schedule
Medical insurance
Sports
Corporate social events
Professional development opportunities
Job Description
We are looking for a Senior Automation QA Engineer (Python) with hands-on experience in testing Big Data or data platform projects. The main goal of the project is to modernize and scale an enterprise data platform by migrating the existing on-premise HDFS and Hive-based ecosystem to a modern cloud-based architecture, improving scalability, performance, and data processing efficiency.
Responsibilities
- Conduct functional testing and code validation to ensure quality and stability of data pipelines.
- Test migration results to confirm data accuracy, completeness, and reliability.
- Perform data quality checks and ensure consistency across systems and tools.
- Use SQL and analytics tools to analyze and validate processed or migrated data.
- Develop and maintain automated tests and integration scripts in Python.
- Collaborate with Data Engineers to troubleshoot issues, validate fixes, and maintain high data quality standards.
- Document testing outcomes, report defects, and contribute to improving overall QA processes.
- Proven experience as an Automation QA Engineer, ideally within Big Data or data platform projects.
- Strong background in functional testing, code validation, and data verification.
- Proficiency in Python for writing and maintaining integration and automation tests.
- Good understanding of data analytics — able to analyze results, interpret metrics, and validate transformations using SQL, Jupyter Notebooks, or Apache Superset.
- Experience in validating the quality and consistency of data and tools used within pipelines.
- Excellent communication and collaboration skills within distributed teams.
- ACE experience preferred (to ramp up faster with existing tools and processes).
- Familiarity with LLMs (e.g., Claude) and AI agent workflows is a plus.
- Basic understanding of Big Data ecosystem components such as Apache Spark, Flink, HDFS, Iceberg, and AWS
- Readiness to evening’s calls till 21:00 Kyiv time
- English level: Upper Intermediate or higher
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.