>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 (BigQuery) 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

Data Quality Engineer