Overview
A Quality Assurance Engineering (QE) Lead possesses expertise in transforming traditional QA processes into a QE model, leveraging AI for test case authoring and automation, and integrating testing within the DevOps pipeline to drive continuous improvement and engineering excellence. Supports the organization’s vision to cultivate a culture of quality, shifting testing left within the entire software development lifecycle and delivers consistent and value-added solutions aligned with business needs/goals. Promotes continuous learning and staying ahead of industry trends in quality engineering and AI and mentors a high-performing team to deliver scalable, reliable testing solutions.
Major Accountabilities
Quality Engineering Responsibilities:
- Lead the transformation of our existing QA function into a mature, engineering-focused, high-impact Quality Engineering practice that emphasizes defect prevention over detection.
- Leverage AI/ML techniques for test case authoring, automation, execution optimization, defect prediction, and predictive quality insights.
- Optimize advanced test automation frameworks and work with DevOps to integrate testing seamlessly into CI/CD pipelines to enable rapid, continuous deployment.
- Partner with Business teams/analysts, project managers, development teams, and QA to define comprehensive testing strategies and ensure complete coverage.
- Facilitate cross-functional meetings and workstreams to align on business needs and ensure the delivery of high-quality solutions.
- Develop and maintain robust automated test scripts across various types of testing, including functional, integration, regression, performance, and API testing
- Lead defect triage activities, facilitating cross-functional collaboration with business stakeholders, implementation partners (both internal and external), and development teams to drive timely resolution and closure of defects.
- Develop QA artifacts - test plans, requirement traceability matrices, and test acceptance reports - and manage the approval workflow among relevant stakeholders
- Establish key performance indicators (KPIs) for the QE function and regularly report on quality metrics, using data driven insights to guide continuous improvement efforts.
Lead Responsibilities
- Lead a team of employees/consultants
- Work with onsite and offshore team members to delegate, prioritize and manage testing tasks and deliverables
- Mentor and guide team members on modern quality engineering practices and discover training needs.
- Monitor team performance and report on metrics
- Ensure that the team is consistently delivering quality solutions to the highest standards
- Verify that the team is adhering to our commitment of principles and practices
- Understand and communicate process methodologies used in the bank
- Provide guidance in planning and executing assigned tasks
- Communicate timely, content relevant information to stakeholders including escalation of key issues and risks
Education/Experience/Skills/Knowledge
Education: Bachelor's degree in Computer Science, Engineering, Accounting, Finance, or a related field, or equivalent work experience, is required
Experience
Minimum of 7 years of software quality assurance/quality engineering experience in agile development environments in a large, regulated financial services (preferably banking) environment is required
Minimum of 3 years in a lead role
Skills & Knowledge
- Working knowledge of Financial domain and Capital Markets with Front Office/Back Office operational is highly desirable
- Working knowledge of Workday GL, HCM and Payroll is nice to have
- Proven track record of driving QE transformations and implementing AI in testing.
- Proficiency with automation tool stack: UiPath, Selenium, Playwright, FitNesse, or equivalent automation skills that proves ability to design, test, and debug automation code.
- Strong understanding of DevOps principles, CI/CD pipelines, and tools.
- Knowledge of TDD (Test Driven Development) and BDD (Behavior Driven Development)
- Working knowledge of complex SQL and experience with ETL processes.
- Strong knowledge of Object-Oriented Programming (OOP) concepts and proficiency in at least one programming language (eg: Python, Java, Java Script)
- Knowledge of robotic process automation (RPA) concepts
- Experience with industry standard testing and defect management tools (e.g. XRAY, ALM, JIRA, Confluence)
- Deep understanding of Agile principles and practices, including Scrum and Kanban
- Knowledge of the Scaled Agile Framework and experience working within an ART is preferred
- Excellent troubleshooting skills to identify root cause of complex issues required
- Strong time management skills and ability to juggle priorities with a history of meeting commitments
- Critical thinker with strong analytical and problem-solving skills
- Excellent verbal and written communication skills
- Ability to perform on high visibility initiatives and prove a dire