SME Testing

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)
• 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