Technology Solutions Pay Details:
$125,500 - $154,000 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually. TD is committed to providing fair and equitable compensation opportunities to all colleagues. 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. Role Summary As a lead software engineer, you are accountable for shaping and delivering end-to-end solutions for enterprise-grade platforms and complex initiatives. You set technical direction, define and govern architecture, and lead delivery execution for a specific solution area while influencing adjacent domains. You are hands-on and outcome-driven: designing and building critical path components, raising engineering standards, and scaling team effectiveness through mentorship, patterns, and automation.
You also pioneer responsible AI-assisted engineering by establishing guardrails, validations, and governance that enable speed without compromising quality.
This opportunity is with the Enterprise Data Management Office (EDMO), where you will deliver Data Catalog services as a product, driving enterprise-wide data discovery, governance, and self-service access to trusted data assets.
An end-to-end technical solution is delivered predictably with strong SDLC discipline, from design to build, test, deploy and operate.
trade-offs are explicit and risk-managed
Cloud architecture and infrastructure decisions support scalable, resilient, secure and cost-effective platform growth across diverse deployment environments
Engineering quality improves quarter-over-quarter through standards, automation and coaching across security, performance and maintainability
Teams ship faster with confidence due to reusable patterns, platform capabilities and AI-enabled workflows with robust guardrails.
Customer
Drive hands-on engineering and modernization: deliver critical components, resolve bottlenecks and implement target-state architecture with incremental, de-risked migration strategies.
Ensure resilient, scalable and efficient platforms: define and validate NFRs, automate delivery, manage dependencies and continuously improve performance, availability and cost efficiency.
Lead cloud architecture and engineering decisions across diverse cloud environments, selecting scalable infrastructure patterns, deployment models and integration approaches that align with enterprise standards.
AI Workflow Innovation & Governance

- Champion AI-assisted development using modern copilots and LLM agents to accelerate delivery while maintaining enterprise-grade standards.
- Design and roll out AI guardrails, including approved use cases, prompt patterns, code provenance expectations and documentation standards.
- Implement validation pipelines for AI-generated code, including linting / formatting, unit and integration tests, SAST / DAST, dependency scanning, secret detection and architectural rules.
- Define human-in-the-loop review requirements, including code review checklists, threat modelling and design reviews for high-risk changes.
- Establish a repeatable AI workflow for the team, including task decomposition, generation, verification, refactoring and documentation, and measure cycle-time impact.
- Promote responsible use across privacy, data handling, IP considerations, auditability and compliance with internal policies and external regulations.

Ensure governance, compliance and risk alignment: adhere to enterprise frameworks,



drive approvals and manage policies in line with business priorities and risk appetite.
Drive quality and operational excellence: enforce shift-left quality, lead design and code reviews, and oversee release readiness and operational gating.
Optimize performance and efficiency: lead enterprise-level analysis, drive remediation and continuous improvement, reduce costs through FinOps practices and integrate emerging trends and regulatory needs.
Scale team impact through enablement: establish patterns, reference implementations, documentation and coaching over individual heroics.
Mentor and elevate engineering excellence: provide hands-on technical guidance, unblock complex issues, lead knowledge sharing through RFCs, guilds and reviews, and drive continuous learning.
Foster a high-performing, inclusive team: promote quality, innovation and collaboration; communicate risks proactively; Acts as a primary subject matter expert across multiple technical areas from design, support and solutions perspectives.
Works independently and / or autonomously as a senior lead across a diverse range of complex tasks and operational support of solutions.
Generally reports to a Senior Manager, Engineering.
Qualifications & Technical Requirements
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.
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, containerization, infrastructure-as-code, resiliency patterns, observability and secure enterprise deployment.
Data Troubleshooting & Quality: Strong ability to investigate and resolve data discrepancies, missing or duplicate records, broken relationships, schema changes, ingestion failures, performance issues, and source-to-target reconciliation problems, with appropriate data-quality controls.
Data Consumption & Integration: Experience designing curated datasets, APIs, scheduled extracts and event-based interfaces that enable downstream applications and users to consume data
AI tooling fluency:



practical experience with coding copilots / LLM agents and a vision for safe integration into enterprise workflows.
Senior Technical Leadership: Ability to independently own complex development work while providing hands-on technical guidance to junior and intermediate developers through solution design, development patterns, troubleshooting, code reviews, testing, documentation, and knowledge sharing.
PostgreSQL, SQL, Python, REST/Graph APIs, Kafka, Batch/File Processing, Azure, Databricks/PySpark, Git & CI/CD, Knowledge Graph / Graph Databases
Experience in data management, data governance, data cataloging or metadata platforms is a plus.
Hands-on familiarity or integration experience in data management, data governance, metadata or catalog platforms, including DataHub, OpenMetadata, Collibra, or comparable solutions is preferable.
Practical knowledge of security and compliance engineering concepts, including RBAC, ABAC, SSO/MFA, secrets management, audit logging, access governance, network controls, and secure configuration baselines.
Pandas experience for data analysis, profiling, transformation or automation use cases is a plus.
Deep experience designing and operating solutions across Azure, AWS or hybrid cloud environments, including managed services, container platforms and scalable infrastructure patterns.
Familiarity with responsible use of coding copilots or AI-assisted developer workflows.
Undergraduate degree, Post Graduate degree or Technical Certificate.

- Strong academic background, such as computer science or engineering.
- Graduate degree nice to have.
- TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being advantages, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. We’re delighted that you’re considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we’re committed to providing the support our colleagues need to thrive both at work and at home.
If you’re interested in a specific career path or are looking to build certain skills, we want to help you succeed. You’ll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.
If you’re passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.
Here at TD, we hire and develop the best.
Training & Onboarding
We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role.
We do our best to communicate outcomes to all applicants by email or phone call.
Please let us know if you’d like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.
Language Requirement (Quebec only):

📌 Software Engineer I (Temporary) (Toronto)
🏢 TD Bank
📍 Toronto