Role: Test Automation Engineer – ETL & Data Analytics Location(s): Charlotte NC (highly preferred) - will consider Irving TX or Chandler AZ Term: 24 month contract (possibility of contract to hire) Compensation: $130,000 range (CANNOT work Corp to Corp) Job Summary: We are seeking a QA Test Automation Engineer with a strong background in ETL testing and data validation to automate testing for data pipelines between Excel spreadsheets and BI dashboards (Power BI/Tableau). The ideal candidate will have hands-on experience in Python-based test automation and a solid understanding of data workflows within financial services. Key Responsibilities: + Design, develop, and maintain automated test scripts to validate ETL processes from Excel files to dashboards (Power BI/Tableau). + Conduct data validation, transformation checks, and reconciliation testing to ensure end-to-end data integrity. + Build reusable Python-based automation frameworks to test data pipelines and support continuous quality assurance. + Write and execute SQL queries for backend data validation. + Identify and troubleshoot data discrepancies, schema mismatches, and transformation errors across systems. + Collaborate with data engineers, BI developers, and QA teams to ensure robust coverage across data workflows. + Integrate automated tests into CI/CD pipelines using tools like GitHub Actions, Jenkins, or similar. + Document test plans, test cases, and automation processes to support audit and compliance requirements. Qualifications: + 5+ years of experience in QA automation, with recent focus on ETL processes and data validation. + 2+ years of experience working in the financial services or banking industry. + Strong hands-on experience with Python for test automation scripting. + Proficiency in SQL for data querying and validation. + Experience working with Excel-based data workflows, including data parsing and transformation validation. + Familiarity with Power BI and/or Tableau, including validating data accuracy in dashboards. + Understanding of data quality principles, including schema validation, reconciliation, and transformation logic. Preferred Skills: + Experience with Selenium or Cypress for UI automation, particularly to validate end-to-end data presentation. + Familiarity with data quality frameworks like Great Expectations or custom Python validators. + Exposure to cloud ETL platforms (e.g., Azure Data Factory, AWS Glue). + Knowledge of data observability and anomaly detection tools (e.g., Soda, Monte Carlo, Datafold) ManpowerGroup is committed to providing equal employment opportunities in a professional, high quality work environment. It is the policy of ManpowerGroup and all of its subsidiaries to recruit, train, promote, transfer, pay and take all employment actions without regard to an employee's race, color, national origin, ancestry, sex, sexual orientation, gender identity, genetic information, religion, age, disability, protected veteran status, or any other basis protected by applicable law.