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Added 27 mins ago
Senior Financial Accountant - Permanent - 19495
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Full-time
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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.
Added 1 hour ago
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Data Engineer II - CPB Data Curation

Toronto, ON, Canada

Pay: $81,600 - $115,200 CAD
Job type: Full-time
Apply by: Oct 23, 2026
Experience: 3–5 years of relevant experience.
Posting language: English
Posted: Sep 23, 2026

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Original job description

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

JOB DESCRIPTION SUMMARY

Provide a broad range of data engineering functions, including data modeling, data quality, data profiling, data acquisition and ingestion, extract, transform and load (ETL), metadata enrichment and management, data provenance and lineage, and other specialized data management functions.

Job Description

CUSTOMER

Perform data analysis and assess data management requirements for a specific Platform or Journey, including complex analysis involving multiple pods or products.
Maintain expert knowledge of upstream data, including knowledge provided through data profiling, data quality reporting, and the production of metadata.
Support the acquisition and ingestion of data.
Articulate complex, large-scale and high-impact technical design and development details to non-technical business partners.
Elicit, analyze and understand business and data requirements to develop complete business solutions, including data models (entity relationship diagrams and dimensional data models), ETL and business rules, data lifecycle management, governance, lineage and metadata.
Ensure data is maintained in compliance with enterprise data standards, policies and guidelines.
Develop and maintain complex data models using industry-standard modeling tools.
Develop and maintain complex ETL jobs and frameworks using the Bank's standard tools.
Provide support to development and testing teams to resolve data issues, including escalation support for complex issues.
Support partners and stakeholders in interpreting and analyzing data.
Analyze and understand business and data requirements to develop complete ETL solutions under the guidance of senior peers and tech leads.

INTERNAL / INTERNE

Build effective working relationships within own pod and across partner teams to encourage collaboration on all pod deliverables.

SHAREHOLDER

Coordinate with technology work teams and stakeholders to ensure overall delivery success.
Support the QA team with data analysis and investigations of complex issues/test cases as part of SIT/UAT/PAT testing.
Provide oversight on post-implementation activities during the warranty period.
Execute and approve code check-in/check-out into the source code repository as part of source code management.
Work closely with Release Management teams to support code packaging and deployment (CI/CD) into higher environments.
Be the lead participant in application design and code reviews.
Raise ServiceNow requests and work with the Change Management team to support release management activities.
Lead data engineering initiatives and capabilities, including data governance principles and how they apply across the organization.
Ensure metadata and data lineage are captured and compatible with enterprise metadata and data management tools and processes.
Adhere to and contribute toward standard secure coding practices to ensure applications are free of common coding vulnerabilities.
Ensure technical decisions, technical risks and lessons learned are identified and clearly documented, with enhancements implemented accordingly.
Protect the interests of the organization by identifying and managing risks and escalating non-standard, high-risk activities as necessary.
Adhere to internal policies/procedures and applicable regulatory guidelines.

INTERNAL / INTERNE

Keep current on emerging trends/developments and grow knowledge of the business, related tools and techniques.
Enable team members by sharing knowledge and leveraging engineering best practices.

EMPLOYEE / TEAM

Participate fully as a member of the team and support a positive work environment that promotes service to the business, quality, innovation and teamwork, while ensuring timely communication of issues and points of interest.
Provide thought leadership and/or industry knowledge for data engineering best practices and participate in knowledge transfer within the team and business unit.
Keep current on emerging trends/developments and grow knowledge of the business, related tools and techniques.
Participate in personal performance management and development activities, including cross-training within own team.
Keep others informed and up to date about the status/progress of projects and all relevant or useful information related to day-to-day activities.
Actively mentor and enable team members by sharing knowledge and leveraging engineering best practices.
Support the team by providing guidance and proactively identifying and resolving issues.
Lead, motivate and develop relationships with internal and external business partners/stakeholders to develop productive working relationships.
Contribute to a fair, positive and equitable environment that supports a diverse workforce.
Act as a brand ambassador for your business area/function and the Bank, both internally and/or externally.

BREADTH & DEPTH

INTERNAL / INTERNE

Advanced knowledge of data engineering frameworks, technologies, tools, processes, patterns and procedures, including how they impact other technology areas such as Architecture or Infrastructure.
Perform complex technical tasks independently.
Advanced knowledge of TD applications, systems, networks, innovation, design activities, business, organization, best practices and standards.
Design and develop to meet business and technical requirements; analyze, adapt, integrate, code, test, debug and execute.
Use and evolve established patterns to solve complex problems; lead the development of new patterns where necessary.
May be recognized as a subject matter expert in areas directly related to key accountabilities.

Experience And/Or Education

Hands-on proficiency in Java/PySpark, Python and SQL, with experience in Azure ADB, ADF and Bitbucket (GitHub).
Solid technical skills in investigating ETL design, optimizing ETL workflows, mitigating risks and ensuring data accuracy - key functions that directly impact business outcomes.
Experience leveraging GitHub Copilot to enhance development productivity and code quality is an asset.
Degree, postgraduate degree or technical certificate in Data or a related discipline (e.g., Computer Science, Engineering), or equivalent practical experience.
3–5 years of relevant experience.

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

Develop and maintain complex data models, ETL jobs, and data engineering frameworks, while supporting data acquisition, quality, governance, metadata, and lineage. Collaborate with business and technology partners, support testing and releases, review code, resolve complex data issues, and contribute to secure engineering practices and team development.

Requirements

Requires hands-on proficiency in Java/PySpark, Python, SQL, Azure Databricks, Azure Data Factory, and Bitbucket or GitHub, along with experience investigating and optimizing ETL workflows and ensuring data accuracy. Candidates should have a degree, postgraduate degree, technical certificate in data or a related discipline, or equivalent practical experience, and 3–5 years of relevant experience.

Skills

Java
PySpark
Python
SQL
Azure Databricks
Azure Data Factory
Bitbucket
GitHub
Data Modeling
ETL
Data Quality
Data Profiling
Data Governance
Metadata Management
Data Lineage
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 Engineering
Java
PySpark
Python
SQL
Azure Databricks
Azure Data Factory
Bitbucket
GitHub
GitHub Copilot
ETL
Data Modeling
Entity Relationship Diagrams
Dimensional Data Models
Data Quality
Data Profiling
Data Acquisition
Data Ingestion
Metadata Management
Data Provenance
Data Lineage
Data Governance
Data Lifecycle Management
Secure Coding
Code Reviews
CI/CD
Source Code Management
SIT/UAT/PAT Testing
Release Management
Banking

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