Work

Location:
Toronto, Ontario, CanadaHours:37.5Line of Business:Technology SolutionsPay 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.
CUSTOMERPerform data analysis and assess data management requirements for a specific Platform or Journey, including complex analysis involving multiple pods or productsMaintain expert knowledge of upstream data, including knowledge provided through data profiling, data quality reporting, and via the production of metadataSupport the acquisition and ingestion of dataArticulate complex, large scale, and high impact technical design and development details to non-technical business partnersElicit, 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 metadataEnsure data is maintained in compliance with enterprise data standards, policies, and guidelinesDevelop and maintain complex data models using industry standard modeling toolsDevelop and maintain complex ETL jobs and frameworks using the Bank's standard toolsProvide support to the development and testing teams to resolve data issues, including escalation support on complex issuesSupport partners and stakeholders in interpreting and analyzing dataBuild effective working relationships within own pod and across partner teams to encourage collaboration on all pod deliverablesSHAREHOLDERCoordinate with technology work teams such as ITS, ARE, Architecture, Enterprise Protect etc. to ensure overall delivery successSupport the QA team with data analysis/investigations of complex issues/ test cases as part of SIT/UAT/PAT testingProvide oversight on post implementation activities during the warranty periodExecute & approve code check-in/ check-out into source code repository as part of source code managementWork closely with ITS/ ARE teams to support code packaging & deployment (CI & CD)



into higher environmentsBe the lead participant in the design & architecture reviews or the applicationRaise service-now requests and work with the change management team to support release management activitiesLead data engineering initiatives and capabilities, data governance principles and how they apply across the organizationEnsure metadata and data lineage is captured and compatible with enterprise metadata and data management tools and processesAdhere & contribute towards standard security coding practices to ensure application is free of most common coding vulnerabilitiesEnsure technical decisions, technical risks and lessons learned are identified, clearly documented and enhancements are accordingly implementedProtect the interests of the organization – identify and manage risks, and escalate non-standard, high-risk activities as necessaryAdhere to internal policies/procedures and applicable regulatory guidelinesKeep current on emerging trends/ developments and grow knowledge of the business, related tools, and techniquesEnable team members by sharing knowledge and leveraging engineering best practices.
EMPLOYEE / TEAMParticipate fully as a member of the team, support a positive work environment that promotes service to the business, quality, innovation and teamwork and ensure timely communication of issues/ points of interestProvide thought leadership and/ or industry knowledge for Data engineering best practices and participate in knowledge transfer within the team and business unitKeep current on emerging trends/ developments and grow knowledge of the business, related tools and techniquesParticipate in personal performance management and development activities, including cross training within own teamKeep others informed and up-to-date about the status / progress of projects and / or all relevant or helpful information related to day-to-day activitiesA

📌 Data Engineer II (Toronto)
🏢 TD
📍 Toronto