QA Automation Lead [gn] Data Intelligence at Actian — AI Jobs | Neura Market

About This Role

The QA Automation Team is the ultimate guardian of our platform’s reliability, scalability, and deployment velocity. In a complex, data-heavy ecosystem, manual testing is a bottleneck; continuous, intelligent, and bulletproof automation is the only way forward.

We are looking for a QA Automation Lead who will architect, scale, and own our automated testing strategy end-to-end. You are not a passive test-case writer or a mere script executor; you are a highly technical, proactive engineer who thrives on breaking complex distributed systems, designing robust testing frameworks, and enforcing a culture of absolute quality. You will lead a dedicated team of automation engineers, embed quality gates directly into our CI/CD pipelines, and use data-driven metrics to eliminate regressions before they ever reach production.

Core Responsibilities:

End-to-End Testing Infrastructure: Design, scale, and maintain robust automation frameworks capable of testing the complex SaaS and distributed data architectures of the Actian Data Intelligence Platform.

Pipeline Integration: Embed automated test suites seamlessly into the CI/CD pipeline (GitHub Actions/Jenkins) to achieve true continuous integration and rapid feedback loops.

Advanced Testing Topologies: Move beyond basic UI testing. Drive deep integration, API, performance, resilience, and data-integrity automation across the entire product stack.

Technical Anchor: Act as the ultimate technical authority for the QA automation squad, establishing clean code standards for test scripts, conducting rigorous code reviews, and minimizing framework technical debt.

Upskilling & Accountability: Coach junior automation engineers and guide functional QA testers in transitioning toward automated practices, ensuring everyone owns their automation targets.

Resource Optimization: Allocate engineering capacity effectively across feature testing, framework enhancement, and technical debt reduction.

Release Gatekeeper: Own the final quality sign-off for platform releases. Have the technical authority and conviction to halt deployments if quality thresholds are not met.

Cross-Functional Bridge: Collaborate closely with Product Management, Core Engineering, and DevOps to understand new features early, mapping out automation strategies before the code is written.

Defect Triage Collaboration: Partner with the Sustaining Engineering team to analyze production leaks, quickly writing automated tests to reproduce bugs and guarantee they never regress.

Flakiness Eradication: Treat flaky tests as a critical system anomaly. Track, isolate, and eliminate them to maintain absolute trust in the automation suite.

Actionable ROI: Track and report on key QA operational metrics (Test Coverage, Automation Pass Rates, Execution Time, and Defect Leakage Rate) to optimize delivery speed.

AI-Driven Testing: Pioneer the usage of modern AI tools to accelerate test case generation, optimize test suites, and intelligently predict defect hot-spots.

Qualifications & Profile:

Technical Background: Strong background as a Senior SDET (Software Development Engineer in Test) or QA Automation Lead, with proven experience testing complex enterprise SaaS, distributed systems, big data engines, or data platforms.

Automation Mastery: Deep expertise in coding languages (Java, Python, or Go) and modern testing frameworks (e.g., Playwright, Cypress, Selenium, or custom-built frameworks). Exceptional SQL skills and API testing expertise are mandatory.

Extreme Ownership: Exceptional proactive behavior. You do not wait for code to be delivered to think about testing. You anticipate regressions, challenge architectural assumptions, and aggressively push for built-in quality.

CI/CD & Infrastructure Savvy: Hands-on experience with Docker, Kubernetes, cloud platforms (AWS/Azure/GCP), and version control workflows (GitHub). You understand how infrastructure impacts application stability.

AI & Innovation Adaptability: Savvy on using AI assistants and generative AI tools to write smarter test suites, mock data, and analyze test failures efficiently.

Communication: Exceptional verbal and written English communication skills. Ability to stand your ground on quality metrics while maintaining collaborative alignment with engineering leadership.

What We Offer:

The chance to be part of an innovative, fast-growing company making a significant impact in the data management space.
Collaboration with a passionate and diverse team.
Competitive salary and benefits package.
Flexible work arrangements (remote or hybrid).
Opportunities for professional growth and development.

Why Join Us? At Actian, we are passionate about innovation and teamwork. This role is perfect for someone who thrives in a dynamic environment, loves creating an efficient and welcoming workspace, and enjoys working closely with a talented team.

Interested? We’d love to hear from you! Let’s discuss how you can contribute to our success while growing your career with us.

We value diversity at our company. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying.

Tasks

•End-to-End Testing Infrastructure: Design, scale, and maintain robust automation frameworks capable of testing the complex SaaS and distributed data architectures of the Actian Data Intelligence Platform.
•Pipeline Integration: Embed automated test suites seamlessly into the CI/CD pipeline (GitHub Actions/Jenkins) to achieve true continuous integration and rapid feedback loops.
•Advanced Testing Topologies: Move beyond basic UI testing. Drive deep integration, API, performance, resilience, and data-integrity automation across the entire product stack.
•Technical Anchor: Act as the ultimate technical authority for the QA automation squad, establishing clean code standards for test scripts, conducting rigorous code reviews, and minimizing framework technical debt.
•Upskilling & Accountability: Coach junior automation engineers and guide functional QA testers in transitioning toward automated practices, ensuring everyone owns their automation targets.
•Resource Optimization: Allocate engineering capacity effectively across feature testing, framework enhancement, and technical debt reduction.
•Release Gatekeeper: Own the final quality sign-off for platform releases. Have the technical authority and conviction to halt deployments if quality thresholds are not met.
•Cross-Functional Bridge: Collaborate closely with Product Management, Core Engineering, and DevOps to understand new features early, mapping out automation strategies before the code is written.
•Defect Triage Collaboration: Partner with the Sustaining Engineering team to analyze production leaks, quickly writing automated tests to reproduce bugs and guarantee they never regress.
•Flakiness Eradication: Treat flaky tests as a critical system anomaly. Track, isolate, and eliminate them to maintain absolute trust in the automation suite.
•Technical Background: Strong background as a Senior SDET (Software Development Engineer in Test) or QA Automation Lead, with proven experience testing complex enterprise SaaS, distributed systems, big data engines, or data platforms.
•Automation Mastery: Deep expertise in coding languages (Java, Python, or Go) and modern testing frameworks (e.g., Playwright, Cypress, Selenium, or custom-built frameworks). Exceptional SQL skills and API testing expertise are mandatory.
•Extreme Ownership: Exceptional proactive behavior. You do not wait for code to be delivered to think about testing. You anticipate regressions, challenge architectural assumptions, and aggressively push for built-in quality.
•CI/CD & Infrastructure Savvy: Hands-on experience with Docker, Kubernetes, cloud platforms (AWS/Azure/GCP), and version control workflows (GitHub). You understand how infrastructure impacts application stability.
•AI & Innovation Adaptability: Savvy on using AI assistants and generative AI tools to write smarter test suites, mock data, and analyze test failures efficiently.