QA Automation - Manager

Job Description

Key Responsibilities:
•    Define and drive QE strategy aligned with BMO’s Enterprise Risk platform architecture, engineering standards, and transformation roadmap
•    Lead end-to-end QE delivery across manual, automation, and data validation workstreams – including UI, API, ETL, and batch validation
•    Establish and scale automation frameworks for: 
o    UI (Selenium, Cypress, Playwright)
o    API (Rest Assured, Postman, Karate)
o    ETL and backend jobs (Python, SQL-based validation frameworks)
•    Collaborate with development, DevOp, Product teams to implement shift-left testing, test data management, and test coverage alignment
•    Integrate QE into CI/CD pipelines using Jenkins/GitLab and enforce test gating, code quality checks, and coverage thresholds
•    Implement non-functional testing strategies (performance, security, resiliency) using tools like JMeter, OWASP ZAP, and integrate into test automation cycles
•    Evaluate and embed GenAI-driven QE capabilities, including test case generation, self-healing scripts, synthetic test data generation, test and coverage gap analysis etc.
•    Support proposal, RFP, and stakeholder presentations by articulating QE capability maturity, roadmap, and measurable outcomes (KPIs, ROI, coverage)
•    Lead a team of SDETs, QE engineers, and manual testers; foster a culture of quality, reusability, and automation-first
•    Drive continuous improvement initiatives via test metrics, RCA, defect leakage trends, and QE process optimization

Required Skills and Experience:
•    Expertise in architecting scalable and modular test automation frameworks across UI, API, and ETL layers
•    Hands-on with tools: Selenium, Rest Assured, Playwright, Postman, JMeter, Python, SQL, Git, Jenkins, Docker, etc.
•    Strong understanding of DevOps, CI/CD integration, test orchestration, and environment provisioning
•    Experience working in BFSI/Wealth/Capital Markets domain; prior exposure to Enterprise Risk platforms, data governance, or regulatory workflows is a strong plus
•    Exposure to AI/ML/GenAI tools in testing & QE
•    Proven ability to mentor and scale QE teams, establish best practices, and manage client expectations
•    Strong interpersonal skills for stakeholder engagement across BAs, Product Owners, Architects, and Delivery Leads
•    Experience in test data virtualization, synthetic data generation, or data masking
•    Familiarity with compliance testing, audit traceability, and reporting standards in banking environments
•    Understanding of microservices, event-driven systems, and integration patterns
•    Strong communication and stakeholder management skills

Mandatory Competencies