QA Automation Engineering

We are seeking an experienced Senior Python / QA Automation Engineer with strong expertise in Python automation, Playwright, Selenium, API testing, and data validation. The ideal candidate will be responsible for ensuring quality throughout the entire software delivery lifecycle, from validating business requirements to designing, executing, and certifying end-to-end test scenarios. The candidate should have hands-on experience in building scalable test automation frameworks, validating complex data pipelines, testing REST and GraphQL APIs, and integrating automated testing into CI/CD pipelines. Experience with Azure, Databricks, Snowflake, and emerging Generative AI and Agentic AI testing practices is highly desirable. Key Responsibilities Design, develop, and maintain scalable Python-based test automation frameworks using Playwright and Selenium WebDriver. Develop and optimize comprehensive test strategies, test plans, test scenarios, and test cases. Review and validate Business Requirements Documents (BRDs), ensuring requirements are clear, complete, and testable. Map business requirements to acceptance criteria and maintain a Requirements Traceability Matrix (RTM) linking requirements, test cases, and test results. Participate in BRD walkthroughs, requirement reviews, and sign-off meetings with business stakeholders. Design and execute end-to-end testing across data pipelines, including source systems, Databricks/Snowflake transformations, and dashboard UI. Perform data validation across Databricks Unity Catalog schemas and write SQL-based data validation scripts. Develop automated data quality and regression testing frameworks using Great Expectations, Deequ, or custom Python solutions. Validate data completeness, referential integrity, schema evolution, and consistency across raw and curated data layers. Perform functional, integration, regression, and end-to-end testing of REST and GraphQL APIs. Validate API contracts, request and response schemas, status codes, headers, authentication, and authorization. Use tools such as Postman, Bruno, Python Requests, and Swagger/OpenAPI validators for API testing. Test API error handling, edge cases, malformed payloads, rate limiting, timeouts, and 4xx/5xx responses. Perform API performance and load testing using Locust, k6, or JMeter to validate response times, throughput, and concurrency. Validate API versioning, backward compatibility, and deprecation handling. Integrate automated UI, API, and data validation tests into CI/CD pipelines to identify defects early. Collaborate with development, DevOps, data engineering, and business teams to identify, troubleshoot, and resolve defects. Maintain defect tracking, test execution reports, and quality metrics while minimizing escaped defects. Explore testing approaches for Generative AI and Agentic AI applications, including automated validation of AI-driven workflows. Required Skills & Qualifications 8+ years of experience in Python development, QA automation, and software testing. Strong hands-on experience with Python, Playwright, and Selenium WebDriver . Expertise in building and maintaining scalable test automation frameworks. Strong experience in API automation and testing of REST and GraphQL services. Hands-on experience with SQL-based data validation and data quality testing. Experience with Databricks, Snowflake, and data pipeline testing. Strong understanding of test strategies, test planning, test case design, test execution, and defect management. Experience with CI/CD pipelines and automation using Azure DevOps, Jenkins, and GitHub Actions. Hands-on experience with Docker, Git, and DevOps practices. Experience with API testing tools such as Postman, Bruno, Requests, or Swagger/OpenAPI. Knowledge of performance testing tools such as Locust, k6, or JMeter. Strong understanding of requirements traceability, acceptance criteria, regression testing, and defect prevention. Familiarity with cloud concepts, particularly Microsoft Azure. Excellent analytical, troubleshooting, communication, and problem-solving skills. Preferred Qualifications Experience with Generative AI and Agentic AI application testing. Familiarity with AI-driven test automation and validation of LLM-based workflows. Experience with Great Expectations, Deequ, or custom Python-based data quality frameworks. Knowledge of Databricks Unity Catalog and modern data engineering architectures. Experience working in Agile/Scrum and global delivery environments. Interview Requirements In-person interview is mandatory. Candidates must be available to interview in person in Plano, TX. Key Skills Python | QA Automation | Playwright | Selenium WebDriver | API Testing | REST API | GraphQL | SQL | Databricks | Snowflake | Azure | Azure DevOps | CI/CD | Jenkins | GitHub Actions | Docker | Data Validation | Test Strategy | RTM | Postman | Performance Testing | Regression Testing Longfinch Technologies