Senior Data Quality Engineer

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
We are seeking a Senior Data Quality Engineer to join our innovative team. In this role, you will ensure the accuracy, reliability, and performance of data systems through cutting-edge test automation, performance optimization, and advanced validation techniques. You will play a key role in maintaining data integrity and optimizing workflows to support critical business decisions.

• Develop robust Python-based test frameworks for SQL validation, ETL verification, and stored procedure unit testing
• Automate data-driven testing with tools like pytest, Hypothesis, pandas, and tSQLt
• Implement AI/ML models for detecting anomalous behaviors in SQL transactions and for test case generation to cover edge scenarios
• Train Machine Learning models to predict slow queries and optimize database performance through indexing strategies
• Validate stored procedures, triggers, views, and business rules for consistency and accuracy
• Apply performance benchmarking with JMeter, SQLAlchemy, and AI-driven anomaly detection methods
• Conduct data drift detection to analyze and compare staging vs production environments
• Automate database schema validations using tools such as Liquibase or Flyway in CI/CD workflows
• Integrate Python test scripts into CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps)
• Design mock database environments to support automated regression testing for complex architectures
• Collaborate with cross-functional teams to develop scalable and efficient data quality solutions

• 5+ years of working experience in data quality engineering or similar roles
• Proficiency in SQL Server, T-SQL, stored procedures, indexing, and execution plans with a strong foundation in query performance tuning and optimization strategies
• Background in ETL validation, data reconciliation, and business logic testing for complex datasets
• Skills in Python programming for test automation, data validation, and anomaly detection with hands-on expertise in pytest, pandas, NumPy, and SQLAlchemy
• Familiarity with frameworks like Great for developing comprehensive validation processes
• Competency in integrating automated test scripts into CI/CD environments such as Jenkins, GitHub Actions, and Azure DevOps
• Showcase of tools like Liquibase or Flyway for schema validation and database migration testing
• Understanding of implementing AI/ML-driven methods for database testing and optimization

• Knowledge of JMeter or similar performance testing tools for SQL benchmarking
• Background in AI-based techniques for detecting data drift or training predictive models
• Expertise in mock database design for highly scalable architectures
• Familiarity with handling dynamic edge case testing using AI-based test case generation

• Opportunity to work on technical challenges that may impact across geographies
• Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications
• Opportunity to share your ideas on international platforms
• Sponsored Tech Talks & Hackathons
• Unlimited access to LinkedIn learning solutions
• Possibility to relocate to any EPAM office for short and long-term projects
• Focused individual development
• Benefit package:
  • Health benefits
  • Retirement benefits
  • Paid time off
  • Flexible benefits
• Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)