Data Quality Engineer

We are looking for a Data Quality Engineer focused on ETL/ELT testing and DWH/DB quality across cloud platforms. You will craft Python- and SQL-driven automation, integrate tests with CI/CD, and partner with stakeholders to keep pipelines accurate.

Responsibilities

Implement automated test scripts to validate ETL workflows and end-to-end data pipelines Conduct full data validation and reconciliation, including DWH/DB testing on large datasets Partner with data engineers, analysts, and stakeholders to define test strategy and meet data quality standards Develop reusable, scalable test automation frameworks using Python and SQL Connect automated tests into CI/CD pipelines to support continuous testing and delivery Assess data transformation logic and completeness across Azure, AWS, and GCP Support Agile ceremonies by contributing to planning, retrospectives, and story grooming Requirements 4-6 years of professional experience in ETL automation and testing for Data Warehouse/Data Lake environments Strong SQL skills for data validation, reconciliation, and automating quality checks Hands-on Python ability for scripting and developing automation frameworks Experience with one or more Test Automation Frameworks in a delivery setting Exposure to Azure (ADF, ADB), AWS (Glue, Lambda, Redshift), and GCP (Big.

Query) cloud data services Working knowledge of CI/CD tooling and practices, including Jenkins, Git, and Azure DevOps Familiarity with Agile/Scrum processes and team rituals Nice to have Experience using data quality or observability tooling such as Great Expectations or Deequ Basic grasp of data governance and metadata management principles Cloud platform certifications in Azure, AWS, or GCP are a plus