Data Quality Engineer

We are looking for a Data Quality Engineer to build ETL/ELT solutions and DWH/DB systems at scale. You will create Python- and SQL-based test automation, validate DWH/Data Lake pipelines, and embed checks into CI/CD workflows across cloud data services.

Responsibilities

• Design automated test scripts to validate ETL workflows and data pipeline behavior
• Execute end-to-end data validation, reconciliation, and DWH/DB testing across large datasets
• Collaborate with data engineers, analysts, and stakeholders to align test strategies with data quality standards
• Build reusable, scalable test automation frameworks using Python and SQL
• Integrate automated tests into CI/CD pipelines to enable continuous testing and delivery
• Validate data transformation logic and completeness across Azure, AWS, and GCP platforms
• Contribute to Agile ceremonies, including sprint planning, retrospectives, and story grooming
  
  

Requirements

• Professional experience of 4-6 years in data quality engineering, including ETL automation and Data Warehouse/Data Lake testing
• Strong command of SQL for data validation, reconciliation, and test automation routines
• Hands-on knowledge of Python for scripting, utilities, and framework development
• Practical experience with one or more Test Automation Frameworks
• Working exposure to Cloud Data Services across Azure (ADF, ADB), AWS (Glue, Lambda, Redshift), and GCP (BigQuery)
• Solid understanding of CI/CD tools and practices, including Jenkins, Git, and Azure DevOps
• Familiarity with Agile/Scrum methodologies and iterative delivery
  
  

Nice to have

• Experience with data observability or data quality tools such as Great Expectations or Deequ
• Basic knowledge of data governance and metadata management concepts
• Cloud certifications in Azure, AWS, or GCP