Technical Lead

Noida, India

Job Summary

As a Quality Engineer Technical Lead, you will be expected to lead the quality engineering strategy for the team with strong ownership of automation, performance validation, test reliability, and production-quality observability. You will drive and maintain the Automation Suite framework used across the team, define scalable automation practices, strengthen regression and integration coverage, and ensure that quality gates are embedded effectively across delivery pipelines. The role requires strong hands-on exposure to performance testing, troubleshooting distributed applications in Kubernetes environments, and using observability tools such as Datadog and logging frameworks to diagnose issues, improve system reliability, and support faster root-cause analysis. Along with individual contribution, you will mentor engineers, guide test design, improve engineering productivity, support customer escalations, and continuously enhance the overall quality posture of the product.

Job Knowledge, Skill and Qualifications

• Bachelor s degree in computer science, Computer Engineering, Electronics and Communication, or a related discipline, with 7+ years of experience in quality engineering, test automation, performance testing, and technical leadership.
• Strong hands-on experience in designing, developing, maintaining, and scaling automation frameworks for API, UI, integration, regression, and end-to-end test coverage.
• Proven ability to lead an Automation Suite framework for a team or program, including framework architecture, reusable components, test orchestration, reporting, maintainability, and adoption by multiple engineers.
• Good programming skills in Java, Python, JavaScript, or a comparable language used for automation development, test utilities, scripting, and framework enhancements.
• Strong experience with performance testing tools and practices, including load testing, scalability testing, baseline creation, bottleneck identification, trend analysis, and performance regression validation.
• Good troubleshooting exposure in Kubernetes-based environments, including deployments, pods, services, ingress, configuration, resource utilization, logs, and common runtime issues.
• Hands-on exposure to observability and monitoring tools such as Datadog, with the ability to analyze dashboards, metrics, traces, alerts, and service health indicators.
• Strong understanding of logging frameworks and log analysis practices to support debugging, defect triaging, root-cause analysis, and production issue investigation.
• Experience integrating automation suites with CI/CD pipelines and ensuring automated quality gates are reliable, actionable, and aligned with release expectations.
• Exposure to cloud-native applications, microservices, Docker, Kubernetes, and distributed system behavior will be an important factor.
• Strong analytical mindset with the ability to connect automation failures, performance trends, logs, metrics, and deployment behavior to identify issues quickly and accurately.
• Ability to mentor team members, review automation code, improve test design, promote quality ownership, and collaborate effectively with engineering, DevOps, and product stakeholders.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.