Data Engineer II

Work Location and Schedule

• The listed work location is Toronto, Ontario, Canada.
• The stated hours are 37.5.

Pay Details

• The listed base pay range is $81,600 to $115,200 CAD.
• Actual compensation may vary based on skills, experience, knowledge, geographic location, and organizational needs.

Role Overview

Data Solutions

• Perform data analysis and assess data management requirements, including complex analysis across multiple pods or products.
• Support data acquisition and ingestion and maintain knowledge of upstream data through profiling, quality reporting, and metadata.
• Develop data models, ETL, business rules, lifecycle management, governance, lineage, and metadata solutions.
• Develop and maintain complex data models, ETL jobs, and frameworks using standard tools.
• Support development and testing teams in resolving data issues and interpret data for partners and stakeholders.

Delivery and Governance

• Coordinate with technology work teams to support overall delivery success.
• Support complex issue investigations during SIT, UAT, and PAT testing and oversee post-implementation warranty activities.
• Manage source code check-in and checkout and support CI/CD packaging and deployment into higher environments.
• Participate in application design and architecture reviews and support change and release management.
• Lead data engineering initiatives and apply data governance, metadata, and data lineage principles across the organization.
• Follow secure coding practices, document technical risks and decisions, manage risks, and comply with policies and regulatory guidelines.

Team Contribution

• Participate in knowledge transfer, cross-training, performance development, and communication of project status and relevant information.
• Mentor and enable team members by sharing knowledge and engineering best practices.
• Support the team by providing guidance and proactively identifying and resolving issues.
• Build productive relationships with internal and external stakeholders.

Experience and Education

• Degree, postgraduate degree, or technical certificate in Data Management or a related discipline, or equivalent practical experience.
• At least 3 years of relevant experience.
• Working experience with Microsoft Azure, Databricks, PySpark, Python, SQL, and Azure Data Factory.
• Measurable outcomes from using AI to improve productivity.
• Excellent problem-solving, communication, and stakeholder-influencing skills.

Technical Scope

• Advanced knowledge of data engineering frameworks, technologies, tools, processes, patterns, and procedures.
• Ability to design and develop against business and technical requirements and use or evolve patterns to solve complex problems.
• Knowledge of data governance, metadata, lineage, source code management, CI/CD, release management, and secure coding practices.

Employee Support

• TD offers development conversations, training programs, mentoring, onboarding, benefits, retirement programs, paid time off, and career development resources.