Technical Business Analyst

Role overview

Business analysis and delivery

• Elicit, analyze, validate, and document requirements; translate business needs into functional and non-functional requirements, user stories, process flows, and acceptance criteria.
• Align solutions with business objectives; assess current and future states and identify process optimization opportunities.
• Perform gap, impact, root cause, and feasibility analyses; support delivery teams as business priorities evolve.
• Facilitate workshops, interviews, and discovery sessions; maintain requirements documents, user stories, workflow diagrams, process maps, and operational procedures.
• Support UAT, SIT, and end-to-end testing.

AI-enabled analysis

• Use generative AI and enterprise AI tools such as Microsoft Copilot or equivalents to support requirements, analysis, documentation, and stakeholder communications.
• Apply prompt engineering and evaluate AI-generated outputs for accuracy, compliance, traceability, security, and business relevance.
• Identify AI-driven process improvements, contribute to AI-enabled delivery practices, and educate stakeholders on practical use cases and responsible AI.

Qualifications and experience

• Requires 4–6 years of business analysis experience in financial services, technology, or large enterprise environments, including 2–3 years using AI-enabled solutions and generative AI in analysis or delivery.
• Experience supporting Waterfall, Agile, or Hybrid delivery; strong SDLC and PDLC knowledge.
• Knowledge of banking systems; LoanIQ is preferred. Familiarity with REST/SOAP services, API integration, architecture concepts, data-flow mapping, and core AWS services is required.
• Experience with cross-functional delivery teams, requirements management, stakeholder engagement, process analysis, solution delivery, workshops, and multiple stakeholders.
• A post-secondary degree in a related field or equivalent practical experience is required.

Technical skills

• Business analysis skills include requirements elicitation, process mapping, impact analysis, stakeholder management, business architecture, and UAT support.
• Data and reporting skills include data analysis and visualization; SQL and Power BI are preferred.
• AI skills include enterprise AI tools, prompt engineering, AI-assisted documentation and testing, responsible AI governance, and productivity automation.
• Delivery tools and methods include Waterfall, Agile, Hybrid, Jira, Confluence, process optimization, and continuous improvement.

Work model

• Hybrid work model with 2–3 days per week in the office.

Compensation

• Published annual salary range is CAD 55,500–120,000; pay type is salaried. Compensation varies with location, skills, experience, education, and qualifications.