We are an Artificial Intelligence Services and Solutions company that focuses on applying Machine Learning, Deep Learning and Advanced Analytics to solve the problems of businesses. Amnet Digital has highly experienced talent from world-leading institutions and technology companies. We have successfully applied AI Technologies in Enterprise Software, Retail, eCommerce and Healthcare. Our digital product engineering teams design and deploy enterprise solutions that are robust, secure and scalable.
Job Level:
Mid-Senior level
Experience:
5-10 years
Location:
Hyderabad, India
About the Role
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We are looking for an experienced QA Engineer with 5-10 years of hands-on experience in validating data pipelines, transformations, and business rules across modern data platforms. In this role, you will design robust test plans, build automated data quality scripts, and ensure the accuracy, completeness, and consistency of data across non-prod and production environments. You will collaborate closely with Data Engineers, Data Analysts, and Solution Architects throughout release cycles to maintain high-quality, reliable data systems.
Your Key Responsibilities
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Validate ETL/ELT pipelines, data transformations, and business rules
Design and execute test plans for data workflows
Build automated data quality and validation scripts
Perform regression, integration, metadata, and lineage validation tests
Review transformations to ensure alignment with business requirements
Conduct end-to-end data pipeline validation across environments
Document test results and maintain QA reports
Participate in release cycles and collaborate with cross-functional teams (DE, DA, Architects)
What To Bring
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Strong experience in data validation testing
Advanced proficiency in SQL
Hands-on Python automation for data QA
Ability to design test cases for ETL/ELT pipelines
Experience with metadata and data lineage validation
Solid understanding of regression and integration testing
Working knowledge of QA frameworks like pytest or Great Expectations
* Understanding of AWS data services
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