Job
Description
We are seeking a visionary Senior Quality Engineer to lead and expand our quality engineering initiatives, the strategic direction, technical leadership, and continuous improvement of our quality engineering services This role combines strategic oversight, technical leadership, and innovative approaches to quality engineering and quality assurance across the organisation As a key influencer, you will drive the development and implementation of quality engineering best practices, automated performance testing frameworks, and advanced quality methodologies across enterprise-scale projects This position offers an exciting opportunity to shape the future of quality engineering through both traditional practices and emerging AI-driven approaches Key Responsibilities: Strategic Implementation Define Quality Engineering Strategy: Establish a comprehensive quality strategy that covers all stages of the software lifecycle, aligns with agile and DevOps methodologies, and integrates both functional and non-functional testing approaches. Process Standardization: Standardize quality engineering practices across the organization, setting guidelines for automation, performance, and security testing, and ensuring adherence to best practices. Resource Allocation: Collaborate with senior leadership on budgeting, resource planning, and tool selection to support the scaling of quality engineering practices across different clients. Innovative Development Tooling Automation: Lead the selection, customization, and deployment of test automation tools (eg, Selenium, WebDriverIO, Playwright, Cypress, and Robot Framework) to enhance efficiency and effectiveness of quality processes. Performance Engineering: Oversee the implementation of performance testing using tools like Locust, JMeter, and K6, integrating monitoring solutions such as Grafana and Prometheus for comprehensive performance analysis. Data-Driven Insights: Implement data visualization and reporting tools, such as PowerBI, to generate actionable insights on quality metrics, test coverage, and product reliability. AI Machine Learning Initiatives: Lead the exploration and integration of AI-driven quality engineering solutions, including predictive analytics for defect detection, intelligent test automation, and anomaly detection. Leverage frameworks and tools like OpenAI, LangChain, and custom machine learning models to develop advanced testing scenarios, automate repetitive tasks, and gain insights from data patterns. Collaborate with data science teams to identify and implement machine learning models that enhance test accuracy and efficiency. Deep Technical Expertise Technical Stack Expertise: Leverage expertise in languages such as Java, JavaScript, C#, Python, NodeJS and frameworks such as React, and Django to provide technical guidance and support quality initiatives across a variety of technology stacks. Cloud DevOps Integration: Integrate quality engineering processes within CI/CD pipelines using Azure DevOps, Jenkins, GitHub Actions, or Concourse, streamlining testing within DevOps workflows. Utilize Kubernetes, Docker, and K9s for environment management and deployment. Database Proficiency: Lead quality engineering strategies for database systems including PostgreSQL, MySQL, MongoDB, and ChromaDB, ensuring data accuracy and application performance. Strategic and Technical Advisory Quality Standards Advisory: Act as a strategic advisor to cross-functional teams, ensuring quality engineering best practices are embedded into project planning, risk management, and development processes. Metrics KPIs for Quality: Define, monitor, and analyze KPIs, including defect density, test coverage, and test execution efficiency, to continuously enhance product quality. Risk Assessment Compliance: Identify and mitigate quality risks, ensuring compliance with industry standards and regulatory requirements. Mentorship and Leadership Team Development Mentorship: Build and mentor the quality engineering team, fostering a culture of continuous learning, technical excellence, and accountability. Stakeholder Communication: Regularly communicate quality engineering goals, progress, and challenges to senior leadership, ensuring alignment between quality objectives and organizational strategy. Talent Acquisition Management: Oversee recruitment and performance management for the quality engineering team, assembling a high-performing team focused on quality and innovation. Autonomy and Empowerment Empowerment Decision-Making: Enable teams to make autonomous, informed decisions on quality engineering strategies, creating a culture of ownership and accountability. Innovation Culture: Encourage experimentation and adoption of emerging quality engineering methodologies, tools, and technologies, promoting a mindset of continuous improvement. Continuous Optimization: Lead retrospectives and post-mortems, ensuring ongoing optimization of quality engineering practices to adapt to business and technological changes. Qualifications Programming & Frameworks: Proficiency in Java, JavaScript, C#, Python, NodeJS, React, and Django. Test Automation Tools: Expertise with Selenium, WebDriverIO, Playwright, Cypress, and Robot Framework. Performance & Monitoring Tools: Experience with Locust, JMeter, K6, Grafana, Prometheus, and PowerBI for performance testing and data visualization. CI/CD and DevOps Tools: Proficient in Azure DevOps, Jenkins, GitHub Actions, and Concourse. Database Systems: Strong knowledge of PostgreSQL, MySQL, MongoDB, and ChromaDB. Testing Frameworks: Skilled in Jest, Junit, Nunit, Xunit, MS Test, Pytest, and TestNG for unit and integration testing. Test Management Tools: Experienced with Jira, Confluence, TestRail, HP ALM, Zephyr, and Xray. Containerization & Orchestration: Proficient with Azure CCS, Kubernetes, Docker, and K9s for container management. AI/ML Technologies: Knowledge of AI and machine learning tools and frameworks, including OpenAI, LangChain, TensorFlow, and scikit-learn, with experience in integrating machine learning models into testing workflows to improve quality predictions, test coverage, and efficiency. Soft Skills: Strategic Vision: Ability to establish a quality engineering vision that aligns with both technical and business goals. Analytical & Problem-Solving: Strong analytical mindset with a proactive approach to resolving quality issues and optimizing processes. Collaboration & Communication: Excellent communication skills for effectively engaging with both technical and non-technical stakeholders. Adaptability: Highly adaptable to changing priorities, with a focus on fostering a culture of continuous improvement. Leadership & Mentorship: Proven ability to lead, mentor, and inspire a team of quality engineers, promoting a culture of accountability and technical excellence.
