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About the Role

As a lead software engineer, you will shape and deliver end-to-end solutions for enterprise-grade platforms and complex initiatives. You will set technical direction, define and govern architecture, and lead delivery execution for a specific solution area while influencing adjacent domains. You will operate confidently across diverse cloud environments, applying deep knowledge of cloud infrastructure, architecture patterns, and engineering practices to design solutions that scale securely and reliably across enterprise platforms. 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 will partner closely with Architecture, Security, Infrastructure, and Product to ensure solutions are resilient, secure-by-design, scalable, observable, and compliant with enterprise standards. You will 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.

Responsibilities

Lead end-to-end solution architecture and delivery: define solution options, align cross-functional stakeholders, own execution and ensure production readiness for complex systems.
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.
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; support hiring, onboarding and equitable practices.

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.
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, containerization, infrastructure-as-code, resiliency patterns, observability and secure enterprise deployment.
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.
Experience designing curated datasets, APIs, scheduled extracts and event-based interfaces that enable downstream applications and users to consume data.
Practical experience with coding copilots / LLM agents and a vision for safe integration into enterprise workflows.
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.
Articulate constraints and trade-offs clearly to engineers, partners and leadership.
Undergraduate degree, Post Graduate degree or Technical Certificate.
Strong academic background, such as computer science or engineering.
5-7+ years relevant experience.

Skills

PostgreSQL
SQL
Python
REST/Graph APIs
Kafka
Batch/File Processing
Azure
Databricks/PySpark
Git & CI/CD
Knowledge Graph / Graph Databases
DataHub
OpenMetadata
Collibra
OpenLineage
W3C PROV-oriented models
Elasticsearch
OpenSearch
RBAC
ABAC
SSO/MFA
Secrets management
Audit logging
Access governance
Network controls
Pandas

Location

Toronto, Ontario, Canada

Work Type

Full-time

Experience Level

Senior
5-7+ years relevant experience

Education Level

Undergraduate degree
Post Graduate degree
Technical Certificate
Graduate degree nice to have

Salary/Compensations

$125,500 - $154,000 CAD

Benefits

Health and well-being benefits
Savings and retirement programs
Paid time off
Banking benefits and discounts
Career development
Reward and recognition programs
Training programs
Competitive benefits plan

About the Company

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores.
Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world.
More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience.
TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing.
Together, we are reimagining what banking can be for our clients, colleagues and communities.

Equal Opportunity

We're committed to providing the support our colleagues need to thrive both at work and at home.
This job opportunity is subject to provincial regulation for employment purposes.
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.
We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals.
Here at TD, we hire and develop the best.
We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role.
We’ll reach out to candidates of interest to schedule an interview.
We do our best to communicate outcomes to all applicants by email or phone call.
Your accessibility is important to us. 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.