Data Quality Engineer

We are looking for a Data Quality Engineer to strengthen data reliability through automated testing of ETL/ELT and DWH/DB flows. You will use SQL and Python to validate large datasets, develop test automation frameworks, and connect checks to CI/CD across Azure, AWS, and GCP.

Responsibilities

• Develop and run automated tests that validate ETL workflows and data pipelines
• Perform end-to-end reconciliation and DWH/DB testing across high-volume datasets
• Coordinate with data engineers, analysts, and stakeholders to define test approaches and uphold data quality standards
• Create scalable, reusable Python and SQL-based test automation frameworks
• Embed automated test execution into CI/CD pipelines for continuous testing and delivery
• Verify transformation logic and data completeness across Azure, AWS, and GCP
• Participate in sprint planning, retrospectives, and story grooming as part of Agile ceremonies
  
  

Requirements

• 4-6 years of relevant experience in ETL automation plus Data Warehouse/Data Lake testing
• Proficiency in SQL to create automated validations and support data quality testing
• Working knowledge of Python for scripting and building automation framework components
• Experience using at least one Test Automation Framework
• Exposure to cloud data services, including Azure (ADF, ADB), AWS (Glue, Lambda, Redshift), and GCP (BigQuery)
• Understanding of CI/CD practices and tools such as Jenkins, Git, and Azure DevOps
• Comfort with Agile/Scrum ways of working in delivery teams
  
  

Nice to have

• Hands-on experience with Great Expectations, Deequ, or similar data observability/data quality tools
• Introductory understanding of data governance and metadata management
• Relevant cloud certifications (Azure/AWS/GCP)