We are seeking a Senior Data Quality Engineer to join our innovative team, where you will drive excellence in database testing, performance optimization, and test automation frameworks. You will leverage advanced Python scripting and database expertise to ensure data integrity and optimize SQL transactions for scalability while working within cutting-edge AI/ML-driven environments.

Responsibilities

• 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
  
  
  

Requirements

• 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
  
  
  

Nice to have

• 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