Job description

Role: QA Engineer with MLOps and Databricks Location: Princeton, NJ HYBRID (3 days a week on-site) W2 ROLE Key Responsibilities: End-to-End Testing: Design, develop, and execute test cases for the complete MLOps pipeline, including data ingestion, ETL processes, machine learning model deployment, and monitoring of web applications. Test Automation: Work with DevOps team to automate test scripts using industry-standard tools for continuous integration/continuous deployment (CI/CD) pipelines and integrate tests into Azure DevOps. Data Validation: Validate data at each stage of the pipeline for accuracy, completeness, and integrity across Azure Databricks, Azure Data Factory (ADF), and other components. Collaborate with Teams: Work closely with MLOps, Data Engineering, and DevOps teams to understand the system architecture and the test requirements for various components. Bug Reporting and Tracking: Identify and report bugs, tracking them through the lifecycle and collaborating with developers to resolve issues effectively. Test Planning & Reporting: Contribute to test planning, preparation, and reporting for various testing stages. Document defects, test results, and test cases in the test management tool. Continuous Improvement: Contribute ideas for improving test coverage, automation frameworks, and overall testing processes to ensure quality at every stage of the pipeline. Version Control and CI/CD: Manage version control for test scripts and integrate them with CI/CD pipelines to ensure seamless deployment and testing. Performance & Load Testing( Nice to have): Perform performance and load testing on data pipelines, APIs, and web applications, ensuring that they scale efficiently and handle large volumes of data. Required Qualifications: Bachelor s degree in Computer Science, Information Technology, Engineering, or a related field. Proven experience (5+ years) in Quality Assurance, with a focus on end-to-end testing in cloud-based environments. Experience in testing data pipelines, SQL, ETL processes, and machine learning workflows. Strong experience in working with Azure Databricks, Azure Data Factory (ADF), and Azure Web Apps. Strong understanding of CI/CD pipelines and experience in integrating automated tests into CI/CD using tools such as Azure DevOps or Jenkins. Solid knowledge of SQL for data validation and verification. Familiarity with version control tools like Git. Exposure to testing microservices and APIs. Strong problem-solving skills and the ability to troubleshoot complex issues. Excellent communication skills with the ability to work collaboratively in a team environment. Familiarity with Agile/Scrum methodologies.

Requirements