Senior QA Test Analyst (Manual + Automation)

INFO ORIGIN INCDenver, CO
$50 - $70Hybrid

About The Position

We are seeking a Senior QA Test Analyst with expertise in both manual and automated testing to join our team. This is a contract position with a hybrid work model, requiring one day per week onsite in Denver, CO. The role involves developing and maintaining automated tests, translating requirements into test cases, designing automation frameworks, and troubleshooting defects. You will also be involved in identifying quality risks, designing performance tests, and working with databases. Strong analytical, debugging, and communication skills are essential.

Requirements

  • Strong knowledge of manual and automated testing, including functional, regression, API, performance, and exploratory testing.
  • Experience with relational and NoSQL databases, test data management, data governance, and production data analysis.
  • Strong debugging, analytical, problem-solving, communication, and collaboration skills.
  • Bachelor’s degree with 3+ years of relevant QA/automated testing experience, or 3+ years of experience as a Business Analyst or Software Engineer.
  • Equivalent relevant experience may substitute for formal education on a year-for-year basis.

Responsibilities

  • Develop and maintain automated tests using Playwright, TypeScript, Java, k6, MCP, and AI-assisted testing.
  • Translate business and functional requirements into comprehensive, efficient test cases using techniques such as boundary value analysis and equivalence partitioning.
  • Design, build, and enhance scalable, reusable automation frameworks using data-driven, keyword-driven, hybrid, and BDD approaches.
  • Analyze logs, HTTP requests/responses, stack traces, browser developer tools, and other diagnostics to troubleshoot defects.
  • Integrate automated testing with Git, CI/CD pipelines, and test management tools such as Zephyr Scale and GitLab.
  • Identify quality risks, assess impact, and implement effective mitigation strategies throughout the SDLC.
  • Design performance test scenarios, user journeys, data parameterization, and load models.
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