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Added 25 mins ago
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- Full-time
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Data Platform Engineering Manager

Toronto, ON, Canada

$115,600 - $163,200 CAD · Full-time

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Job details

Pay: $115,600 - $163,200 CAD
Job type: Full-time
Apply by: Oct 15, 2026
Experience: 8-12+ years of experience in data engineering, data platform delivery, software engineering, cloud data platforms, or related technology roles.
Posting language: English
Posted: Oct 1, 2026

Original job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Technology Solutions

Pay Details:

$115,600 - $163,200 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:

The Data Platform Engineering Manager role is responsible for designing, building, and operating the enterprise technology reference data platform that serves as the foundation for technology governance, reporting, analytics, metrics, and decision-making. Reporting to the Head of Technology Data Management, this role leads the onboarding, integration, transformation, and delivery of technology data from infrastructure, cyber, cloud, AI, and enterprise systems into a Databricks-based data fabric.

The role is accountable for establishing scalable data ingestion patterns, integration frameworks, platform engineering standards, and operational controls that ensure technology data is accurate, accessible, reliable, secure, and consumable. This position plays a critical leadership role in enabling enterprise-wide data products, dashboards, KPIs, risk reporting, and operational insights through modern data engineering and platform capabilities.

KEY ACOUNTABILITIES

Data Platform Strategy & Enablement

Lead the design, implementation, and evolution of the Databricks-based technology reference data platform.

Develop platform standards, engineering patterns, and operating procedures that support enterprise scalability and sustainability.

Establish a modern data ecosystem capable of supporting governance, reporting, analytics, and AI-driven use cases.

Drive platform modernization initiatives that improve performance, automation, resilience, and user experience.

Data Ingestion & System Onboarding

Lead onboarding of technology systems of record into the enterprise data platform.

Design and implement scalable integration patterns including APIs, event-driven architectures, data streaming, and zero-copy data sharing.

Establish standards for source system connectivity, transformation, validation, and data movement.

Partner with source system owners to ensure data is delivered accurately, securely, and efficiently.

Data Engineering & Transformation

Design, build, and manage data pipelines that transform disparate source data into standardized enterprise data assets.

Develop reusable ingestion and transformation frameworks that accelerate onboarding of new data sources.

Implement automated controls to ensure data quality, integrity, completeness, and consistency.

Optimize data processing and storage solutions to support large-scale technology data domains.

Data Operations & Reliability

Establish monitoring and observability capabilities to ensure platform health and data reliability.

Define operational support processes, service-level agreements, and issue management procedures.

Lead remediation efforts for data delivery issues, performance bottlenecks, and platform incidents.

Ensure platform availability, resiliency, and business continuity requirements are met.

Data Security, Controls & Compliance

Ensure compliance with enterprise security, data protection, and regulatory requirements.

Implement access controls, encryption standards, audit logging, and monitoring capabilities.

Partner with Risk, Security, and Compliance teams to support governance objectives.

Ensure adherence to enterprise technology and data management standards.

Enablement of Data Products

Support development and operationalization of technology data products.

Ensure data products are sourced from authoritative systems and delivered through governed engineering processes.

Build reusable data services supporting reporting, analytics, APIs, and business intelligence platforms.

Enable self-service access to trusted enterprise technology data where appropriate.

Partnership & Stakeholder Engagement

Partner with Data Architecture, Governance, Reporting, and Business Intelligence teams to deliver integrated solutions.

Collaborate with Infrastructure, Cybersecurity, Cloud, Engineering, and Enterprise Architecture teams.

Participate in enterprise governance forums and provide technical leadership on platform capabilities and integration approaches.

Influence platform and engineering decisions that improve enterprise data maturity.

Employee / Team Accountabilities

Build and lead a high-performing team of data engineers, platform engineers, integration specialists, and DataOps professionals.

Establish clear team objectives, performance measures, and development plans.

Foster a culture of accountability, innovation, automation, and continuous improvement.

Manage team capacity, prioritization, resource allocation, and delivery commitments.

Ensure engineering teams follow enterprise standards, controls, and best practices.

Develop technical talent and mentoring programs to strengthen engineering capabilities.

Promote collaboration across architecture, governance, analytics, and technology teams.

EDUCATION & EXPERIENCE

Bachelor's Degree in Computer Science, Engineering, Information Systems, Software Engineering, Data Science, or a related discipline.

Master's Degree preferred in Computer Science, Data Engineering, Information Technology, or a related field.

Relevant certifications preferred:

Databricks Data Engineer Professional

Azure Data Engineer Associate

AWS Data Analytics or Data Engineering Certification

Google Professional Data Engineer

Snowflake, Kafka, or Streaming Technology Certifications

ITIL Foundation

8-12+ years of experience in data engineering, data platform delivery, software engineering, cloud data platforms, or related technology roles.

5+ years leading engineering or platform teams in large enterprise environments.

Proven experience designing and implementing enterprise data lakes, data fabrics, or cloud-native data platforms such as Databricks.

Strong experience building APIs, event-driven architectures, streaming platforms, and modern integration solutions.

Hands-on experience developing scalable ETL/ELT pipelines and data transformation frameworks.

Experience with cloud ecosystems including Azure, AWS, or Google Cloud.

Strong understanding of DataOps, observability, monitoring, automation, and platform operations.

Experience supporting enterprise reporting, analytics, AI, and machine learning use cases through modern data platforms.

Experience working in highly regulated organizations with strong governance, security, and compliance requirements.

Excellent stakeholder management, communication, and leadership skills.

Who We Are:

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.

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 role involves designing, building, and operating an enterprise technology reference data platform using Databricks to support analytics, reporting, and AI initiatives. You will lead a team of engineers to establish scalable data ingestion patterns, integration frameworks, and operational controls to ensure data reliability and security.

Requirements

Candidates must have 8-12+ years of experience in data engineering or platform delivery, with at least 5 years in a leadership capacity. A Bachelor's degree in a relevant technical field is required, and proficiency in cloud ecosystems and modern data integration patterns is essential.

Skills

Data Engineering
Platform Engineering
Databricks
Cloud Computing
Data Architecture
API Development
Event-driven Architecture
Data Governance
DataOps
Leadership
Stakeholder Management
ETL/ELT
Data Security
System Integration
Observability
Automation

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 Platform
Databricks
Data Fabric
Data Engineering
Cloud-native
Azure
AWS
Google Cloud
ETL
ELT
DataOps
API
Event-driven Architecture
Data Governance
Cybersecurity
Artificial Intelligence
Machine Learning
ITIL
Data Quality
Observability
Infrastructure
Enterprise Architecture
Business Intelligence
Data Integration
Scalability
Automation
Resilience
Compliance
Risk Reporting
Technology Management

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