Job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Technology Solutions

Pay Details:

$81,600 - $115,200 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:

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

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 via 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, dimensional data models), ETL and business rules, data life-cycle 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 the development and testing teams to resolve data issues, including escalation support on complex issues
• Support partners and stakeholders in interpreting and analyzing data
• Build effective working relationships within own pod and across partner teams to encourage collaboration on all pod deliverables
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