Sr. QA Automation Engineer
Sr. QA Automation Engineer
The Sr. QA Automation Engineer leads automated testing strategy and implementation across Pantomath’s platform, ensuring scalable, reliable, and high-performing solutions. This role involves mentoring, architectural input, and close collaboration with product and engineering teams.
Key Responsibilities
- Design and lead implementation of robust automation frameworks.
- Drive quality initiatives across the full software development lifecycle.
- Own performance, scalability, and reliability testing strategy.
- Collaborate with engineers and product managers to define testing requirements and test plans.
- Lead incident reviews and implement preventative test cases for root causes.
- Mentor junior QA engineers and promote best practices across the QA function.
- Enhance CI/CD automation by integrating test pipelines and metrics dashboards.
Qualifications
Education and Experience
- Bachelor’s degree in Computer Science, Engineering, or related field.
- 5–8 years in QA automation with a focus on complex SaaS systems.
Skills and Competencies
- Expert in JavaScript/TypeScript and automation tools such as Cypress, Playwright, or similar.
- Proficient in testing microservices, APIs, and high-throughput data systems.
- Experience with cloud platforms and performance/load testing tools.
- Strong collaboration, leadership, and communication skills.
- Department
- Engineering
- Role
- QA Automation Engineer
- Locations
- Cincinnati, San Francisco Bay Area, CA
- Remote status
- Hybrid
- Employment type
- Full-time
About Pantomath
Pantomath is an automated data operations platform that addresses the challenges organizations face with data reliability, where manual, time-consuming processes and reliance on tribal knowledge often hinder effective problem resolution.
By automating data monitoring and impact analysis, Pantomath streamlines operations and improves data confidence, quality, and reliability. Enterprises using Pantomath significantly reduce mean time to acknowledgement, mean time to root cause, and mean time to resolution of all data issues across their entire data ecosystem.
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