Data Quality / QA Engineer ____ Remote (Ohio, USA) ...

Job Title: Data Quality / QA Engineer Location: Remote (Ohio, USA) Employment Type: Contract, Long TermPrior experience with Cardinal is highly preferred.Job Overview: We are seeking a highly skilled Data Quality / QA Engineer with strong expertise in C# unit testing, API automation, and Azure DevOps CI/CD pipelines. The ideal candidate will have a background in C# Core API development and experience designing and maintaining data quality frameworks to ensure the reliability, accuracy, and scalability of enterprise data solutions.Key Responsibilities: Design, develop, and maintain automated testing frameworks for APIs, data pipelines, and integrations. Implement unit, integration, and regression tests using xUnit, NUnit, or MSTest frameworks in C#. Collaborate with developers and DevOps engineers to integrate testing within Azure DevOps CI/CD pipelines. Build and maintain C# Core API testing scripts and tools for automation. Conduct data validation, schema verification, and consistency checks across data models and sources. Develop and maintain data modeling and deployment documentation for QA processes. Define and report quality metrics to monitor test coverage, defect trends, and release readiness. Drive improvements in data quality assurance practices through automation and continuous testing. Must-Have Skills: Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field. Overall IT Experience: 9+ Years Strong proficiency in C# and .NET Core API development. Hands-on experience with xUnit, NUnit, or MSTest for automated testing. Expertise in API testing and automation frameworks (Postman, RestAssured, or custom-built). Working knowledge of Azure DevOps CI/CD for test integration and deployment. Experience in data validation, quality matrices, and test documentation. Knowledge of data modeling, ETL validation, and SQL for backend testing. Nice-to-Have Skills: Experience with Selenium, SpecFlow, or Playwright for end-to-end automation. Familiarity with containerization (Docker) and Kubernetes for QA environments. Exposure to data pipeline testing (Databricks, Azure Data Factory, etc.). Understanding of Agile/Scrum testing methodologies.

Created: 2026-04-02