Job Description Insight Global is seeking a highly skilled QA Engineer to join our Data & Analytics team for one of our hardware manufacturing clients. This role will be responsible for ensuring the quality, integrity, accuracy, and reliability of enterprise data solutions, including large-scale data pipelines, ETL/ELT processes, data warehouses, and reporting platforms. Key Responsibilities

•  Design, develop, and execute comprehensive test strategies for large-scale data pipelines, ETL/ELT processes, and analytics platforms.
•  Validate data models, schemas, transformations, and business logic to ensure data accuracy, consistency, and compliance with business requirements.
•  Build and maintain automated data validation frameworks using PySpark, Spark SQL, SQL, and Python.
•  Perform regression, integration, system, and end-to-end testing of cloud-based data solutions.
•  Validate dimensional and relational data models, including fact and dimension tables, ensuring adherence to data modeling best practices.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements

•  4+ years of QA Engineer related experience
•  Experience testing ETL/ELT pipelines and large scale data platforms
•  Experience validating data warehouses, data lakes and analytic ecosystems
•  Hands on Microsoft Fabric Experience