Software Engineer II

Work Location

Toronto, Ontario, Canada

Hours

37.5

Line of Business

Technology Solutions

Pay Details

$81,600 - $115,200 CAD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description

Role Summary

As a Software Engineer II, you provide technical expertise to implement scalable, reliable and secure solutions for EDMO Data Catalog services. You contribute to solutions that operate across diverse cloud environments, applying practical knowledge of cloud infrastructure, deployment patterns and scalable engineering practices. You translate architecture and product requirements into quality software, working independently on complex components while partnering with senior engineers, Architecture, Security, Infrastructure and Product.

You are accountable for detailed design, development, testing and operational support within your assigned solution area. You contribute to engineering standards, automation and reusable patterns, and help improve team delivery through pragmatic technical recommendations and disciplined execution.

You support responsible AI-assisted engineering by applying approved guardrails, using AI tools where appropriate, and validating generated outputs through code review, automated testing and secure delivery practices.

Key Outcomes

• Complex features and components are delivered predictably, aligned to architecture direction and enterprise engineering standards.

• Detailed technical designs, implementation choices and trade-offs are documented clearly enough for review, support and auditability.

• Implemented components align to cloud architecture patterns and support scalable, observable and resilient operation in enterprise cloud environments.

• Code quality, test coverage and maintainability improve through peer review, automation and adherence to secure coding standards.

• Applications operate reliably through effective monitoring, incident support and timely resolution of defects and production issues.

• The team benefits from reusable implementation patterns, documentation and knowledge sharing within the assigned solution area.

Customer

• Develop and document detailed solution designs, acting as an application SME through design and development while ensuring alignment with Architecture.

• Build, test and support complex application components, APIs, integrations and data flows that meet business, technical, performance and security requirements.

• Build and support cloud-ready components, APIs, integrations and data flows using approved infrastructure, deployment and scalability patterns.

• Analyze technical requirements and recommend pragmatic engineering solutions for assigned features, components and platform capabilities.

• Review technical deliverables throughout design and development to identify quality gaps, redesign needs and cross-release impacts.

• Work with technology partners to define metrics, validate performance goals and address application or data issues affecting solution integrity.

AI Workflow Innovation & Governance

• Use approved AI-assisted development tools to accelerate coding, refactoring, testing and documentation within defined enterprise guardrails.

• Validate AI-generated code through peer review, automated tests, linting, dependency checks and secure coding practices before delivery.

• Document prompts, assumptions or generated artefacts when required so outputs remain traceable and supportable.

• Escalate potential privacy, IP, security or data-handling concerns before using sensitive information in AI-assisted workflows.

• Contribute examples, patterns and lessons learned that help the team improve safe use of AI-enabled engineering practices.

Shareholder

• Adhere to enterprise frameworks, methodologies and controls related to software engineering activities.

• Conduct code reviews and contribute to operational readiness reviews, gating and review sign-offs for solution design.

• Identify opportunities to improve quality, reduce cost, automate manual effort and enhance stakeholder experience.

• Protect the interests of the organization by identifying and managing risks and escalating non-standard or high-risk activities.

• Keep current with emerging engineering trends, regulatory expectations and technology practices that may impact assigned solutions.

Employee / Team

• Actively mentor and enable team members by sharing knowledge, engineering practices and practical implementation guidance.

• Participate fully as a member of the team, supporting a positive work environment that promotes quality, innovation, teamwork and timely communication.

• Keep others informed on project status, technical risks, issues and relevant day-to-day delivery information.

• Lead productive working relationships with internal technology partners, product stakeholders and control functions.

• Contribute to a fair, positive and equitable environment and act as a brand ambassador for the business area and the bank.

Breadth & Depth

• Advanced knowledge of a specific domain or range of engineering frameworks, technologies, tools, processes and organizational issues.

• Performs complex to difficult technical tasks independently and works autonomously as a senior contributor on a diverse range of tasks.

• Develops program specifications; adapts, integrates, codes, tests and debugs programs; and is responsible for execution.

• Uses existing procedures to solve routine problems and makes limited exceptions.

• Generally reports to a Senior Manager, Engineering.

Qualifications & Technical Requirements

• Exceptional problem-solving skills with a proven track record diagnosing complex system failures and designing resilient solutions.

• Strong hands-on experience designing normalized, extensible relational data models , including schemas, entities, relationships, keys, constraints, historical/versioned data, and models that can accommodate multiple source structures.

• Knowledge Graph & Graph Database Engineering: Hands-on experience designing and implementing knowledge graph or graph-oriented data models, including nodes, edges, relationship semantics, graph traversal and query patterns, and integrating graph capabilities with PostgreSQL or graph database technologies to support connected-data discovery, lineage, dependency mapping and impact analysis.

• Strong hands-on experience with PostgreSQL, SQL, Python and data engineering, including database schemas, indexing, query optimization, JSON/JSONB where appropriate, transformations, change tracking, and high-volume data processing.

• Proven experience designing and developing reusable ingestion and extraction patterns using REST/Graph APIs, batch/file processing, Kafka/event-driven integration, and incremental processing. Strong understanding of SQL versus NoSQL trade-offs.

• Ability to contribute hands-on to the design and implementation of a data lake , including raw, standardized/ normalized, curated/ consumption layers that can scale for future sources and use cases.

• Advanced CI/CD and DevOps practices: automated testing, release strategies, infrastructure-as-code and environment management.

• Expert knowledge of cloud infrastructure and scalable architecture patterns, including cloud-native services, containeriz