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