Software Engineer II

Role summary

Engineering and delivery

• Develop and document solution designs, acting as an application subject-matter expert and aligning with Architecture.
• Build, test, and support complex application components, APIs, integrations, and data flows to business, technical, performance, and security requirements.
• Build cloud-ready components using approved infrastructure, deployment, and scalability patterns.
• Analyze requirements, recommend engineering solutions, and review deliverables for quality gaps, redesign needs, and cross-release effects.
• Work with technology partners to define metrics, validate performance goals, and resolve application or data issues.

AI workflow and governance

• Use approved AI-assisted development tools for coding, refactoring, testing, and documentation within enterprise guardrails.
• Validate generated code through peer review, automated tests, linting, dependency checks, and secure coding practices.
• Document prompts, assumptions, or generated artifacts when required; escalate privacy, intellectual property, security, or data-handling concerns.
• Share examples and lessons to improve safe AI-enabled engineering practices.

Standards and teamwork

• Follow enterprise engineering frameworks and controls; conduct code reviews and contribute to operational-readiness and design reviews.
• Identify opportunities to improve quality, reduce cost, automate manual work, and enhance stakeholder experience; manage and escalate risks.
• Mentor teammates, share practical engineering guidance, communicate project status and risks, and work effectively with partners and stakeholders.

Technical qualifications

• Strong software engineering fundamentals across backend services, APIs, data modeling, testing, and operational support.
• Experience developing secure, maintainable Python code; TypeScript/Node.js and cloud-native patterns are preferred.
• Knowledge of cloud platforms, cloud-native patterns, infrastructure as code, containers, observability, and secure deployment.
• Working knowledge of CI/CD, automated testing, dependency management, observability, and incident support.
• Able to translate requirements into technical designs, estimates, user stories, and acceptance criteria; communicate technical decisions and trade-offs.

Preferred qualifications and experience

• Data management, data governance, metadata, or data catalog experience is preferred; Collibra or comparable platforms and Pandas are a plus.
• Experience with Azure, AWS, or hybrid cloud, managed services, containerized workloads, secure API integrations, and CI/CD deployment is preferred.
• Practical exposure to coding copilots or LLM-assisted engineering workflows is preferred.
• Undergraduate degree, postgraduate degree, or technical certificate; strong academic background such as computer science or engineering.
• 3–5+ years of relevant experience.

Pay and total rewards

• Listed pay range is $81,600–$115,200 CAD; the posting does not specify a pay cadence.
• Total rewards include base salary, variable compensation, health and well-being benefits, savings and retirement programs, paid time off, and banking benefits.

Hours

• 37.5 hours.