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Data Architect

Toronto, ON, Canada

Pay: $125,500 - $148,000 CADThis role is eligible for a discretionary variable compensation award that considers business and individual performance.
Job type: Full-time
Apply by: Oct 15, 2026
Experience: 10+ years of data engineering or software engineering experience, with the last 3+ in an architecture or technical leadership role.
Posting language: English
Posted: Sep 25, 2026

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Original job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Technology Solutions

Pay Details:

$125,500 - $148,000 CADThis role is eligible for a discretionary variable compensation award that considers business and individual performance.

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:

The Opportunity

Global Transaction Banking is building a modern data platform from the ground up - not patching what exists, but designing what comes next. Data products, real-time pipelines, AI-ready foundations, regulatory reporting, and the APIs that make all of it consumable by the rest of the business.

As Data Architect , you will drive the end-to-end technical architecture for how GTB's data ecosystem is designed, governed, and delivered. You will set the architecture, define the data product and API contracts that surface intelligence to client-facing systems, and provide the technical authority for data platform decisions across the organization.

This is a hands-on architecture role. You will be in the code, in the design reviews, and in the room where data strategy becomes engineering reality.

Mandate: Define and steward the data platform architecture across GTB - ensuring data is trusted, timely, governed, and a genuine engine for analytics, AI, and business outcomes.

Data Platform Architecture

Define the GTB Data Platform architecture - ingestion patterns, data product design, structure, conventions, and multi-zone storage strategy.
Establish architectural standards for batch, micro-batch, and real-time data processing using Apache Spark, Flink, and event-streaming technologies.
Drive the data modelling frameworks - domain-oriented data products, and the metadata and lineage architecture that makes them trustworthy.
Drive architectural decisions on platform scalability, cost optimization, performance tuning, and operational resilience.

Data Products & API Architecture

Define the data product architecture - how data assets are packaged, versioned, published, and consumed across GTB domains.
Design and govern the data API layer - contracts, versioning, access patterns, and the interface between the data platform and consuming applications.
Establish event-driven data distribution patterns using Kafka or Confluent, enabling real-time data availability across GTB systems.
Ensure data APIs meet enterprise security, observability, and reliability standards before they are built.

Governance, Quality & Observability

Own the data governance architecture - metadata management, data lineage, classification, access control, and policy enforcement frameworks.
Define data quality standards and the automated monitoring infrastructure that enforces them at pipeline and product level.
Establish platform observability architecture: pipeline health, data freshness SLAs, anomaly detection, and operational alerting.
Ensure regulatory reporting requirements are embedded into platform design.

AI & Analytics Foundations

Define the architectural foundations for AI and ML workloads on the platform - feature stores, model serving patterns, vector storage, and prompt pipeline infrastructure.
Partner with ML Engineers to ensure the data platform is a reliable, low-latency substrate for Generative AI and LLM-powered capabilities.
Drive adoption of data and AI capabilities that improve operational efficiency, client outcomes, and business decision-making across GTB.

Engineering Standards & Enablement

Establish and maintain data engineering standards, reference architectures, and reusable patterns across the Data Pod.
Lead architectural reviews, spike investigations, and critical platform design decisions.
Drive adoption of DevSecOps, automated testing, data contract testing, and CI/CD for data pipelines.
Mentor Staff and Senior Data Engineers; grow architectural thinking across the team.

Enterprise Architecture Engagement

This role operates within the enterprise architecture governance model and is expected to lead and represent the Data domain through all EA touchpoints:

Process & Accountabilities

Architecture Engagement & Triage - Register new data platform and AI initiatives; scope architecture risk and complexity; route to appropriate review track.
Design Council / Peer Review - Present Data architectural decisions for peer challenge; review and provide input on cross-domain proposals from Channels and Platform.
Architecture Blueprinting & Platform Vision - Own and maintain the GTB Data architecture blueprint; align to enterprise data strategy and multi-year platform roadmap.
Architecture Certificate / APAT Approval - Obtain architecture approval for all qualifying data platform and AI initiatives; ensure designs meet enterprise standards before build entry.
Standards & Controls Alignment - Ensure data platform solutions comply with enterprise data governance, security, privacy, and integration standards; identify and formally manage exceptions.
Business Architecture & Capability Governance - Map data and analytics capabilities to business capability model; participate in capability investment planning and data product roadmap governance.
Delivery Readiness Handshakes (PI / Build Execution) - Confirm architecture completeness at PI planning gates; support delivery teams through architecture queries during build and validate that solutions are built to design.

What We're Looking For

Core Requirements

10+ years of data engineering or software engineering experience, with the last 3+ in an architecture or technical leadership role.
Proven track record designing and delivering production-grade data platforms at enterprise scale - not just contributing to them.
Deep expertise in Databricks - platform architecture, Delta Lake, workspace governance, cluster management, and engineering best practices.
Strong foundation in Apache Spark and large-scale distributed data processing; experience with real-time or streaming architectures.
Solid understanding of modern data architecture: data products, data mesh or domain-oriented design, metadata management, and data lineage.
Hands-on experience with event-driven architectures and streaming platforms (Kafka, Confluent, or equivalent).
Experience with Microsoft Azure and cloud-native data platform delivery.
Comfortable with ambiguity - able to define the path forward when requirements are incomplete and tradeoffs are real.

Nice to Have

Experience with Apache Flink or other stream-processing frameworks.
Familiarity with AI/ML platform patterns: feature stores, model registries, vector databases, LLM integration.
Exposure to regulatory reporting or data governance in a financial services context.
Experience with graph or document data models (Neo4J, MongoDB).

Why Join Us

This is a rare opportunity to do foundational architecture work on a platform that genuinely matters - powering regulatory reporting, client analytics, AI products, and real-time transaction banking capabilities for a major financial institution. You'll have real authority over technical direction, proximity to business outcomes, and a team of strong engineers.

The data problems here are hard, the platform is genuinely interesting, and the decisions you make will shape what GTB can do for the next decade.

Who We Are:

TD Securities offers a wide range of capital markets products and services to corporate, government, and institutional clients who choose us for our innovation, execution, and experience. With more than 6,500 professionals operating out of 40 cities across the globe, we strive to make every interaction, product and experience remarkably human and refreshingly simple. Our services include underwriting and distributing new issues, providing trusted advice and industry-leading insight, extending access to global markets, and delivering integrated transaction banking solutions. In 2023, we acquired Cowen Inc., offering our clients access to a premier U.S. equities business and highly-diverse equity research franchise, while growing our strong, diversified investment bank.

Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards Package
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 benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
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.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.

Colleague Development

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.

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.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role.

Interview Process
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.

Accommodation
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.

We look forward to hearing from you!

Language Requirement (Quebec only):

Sans Objet

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More about this job

Responsibilities

The Data Architect will define and steward the end-to-end technical architecture for the Global Transaction Banking data ecosystem. This includes designing data products, establishing architectural standards for real-time pipelines, and ensuring platform scalability and governance.

Requirements

Candidates must have 10+ years of data or software engineering experience with at least 3 years in an architecture or technical leadership role. Deep expertise in Databricks, Apache Spark, and cloud-native data platform delivery is required.

Skills

Data architecture
Data engineering
Databricks
Apache Spark
Delta Lake
Kafka
Confluent
Azure
Cloud-native data platform
Data governance
Data modeling
API design
Event-driven architecture
Technical leadership
DevSecOps
CI/CD

Benefits

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

Visa sponsorship

Not detected in the job text

Keywords

Data Architect
Data Platform
Databricks
Delta Lake
Apache Spark
Apache Flink
Kafka
Confluent
Azure
Data Mesh
Data Governance
Data Lineage
API
DevSecOps
CI/CD
Generative AI
LLM
Feature Stores
Regulatory Reporting
Cloud-native
Distributed Systems
Metadata Management
Observability
Data Modeling
Micro-batch
Streaming
Architecture Blueprinting
Technical Authority
Financial Services
Transaction Banking

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