Senior Manager Quality Engineering

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: UI (Selenium, Cypress, Playwright) API (Rest Assured, Postman, Karate) ETL and backend jobs (Python, SQL-based validation frameworks) Led a team of 20–30 members while fostering a culture centered on quality, reusability, and an automation-first mindset 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

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