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Added 2 mins ago
AW
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University of Toronto

Data Engineer, Lead

Toronto, ON, Canada

Closing Date: 11/25/2026, 11:59PM ET Employee Group: Salaried Personnel Subarea:PM Appointment Type: Budget - Continuing Schedule: Full-Time Pay Scale Group & Hiring Zone: PM 3 -- Hiring Zone: $97,336 - $113,558 -- Broadband Salary Range: $97,336 - $162,224 Job Category: Information Technology (IT)

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Job details

Pay: Closing Date: 11/25/2026, 11:59PM ET Employee Group: Salaried Personnel Subarea:PM Appointment Type: Budget - Continuing Schedule: Full-Time Pay Scale Group & Hiring Zone: PM 3 -- Hiring Zone: $97,336 - $113,558 -- Broadband Salary Range: $97,336 - $162,224 Job Category: Information Technology (IT)
Apply by: Nov 26, 2026
Posting language: English
Posted: Nov 4, 2026

Original job description

Date Posted: 11/04/2026
Req ID: 50908
Faculty/Division: Institutional Research and Data Governance
Department: Institutional Research and Data Governance
Campus: St. George (Downtown Toronto)
Existing Vacancy: Yes

Description:

The University’s Institutional Research and Data Governance (IRDG) office was formally launched in 2020. In addition to providing leadership and administrative support for the institution’s data strategy, the IRDG office’s mandate is to:

provide data, reporting and analytics services within our distributed institutional research model: lead institution-wide analysis projects, provide training opportunities for divisional analysts, implement new analytics tools and platforms, and improve access to curated institutional data sets
implement an institution-wide Data Governance program to support the University in strategically harnessing data to achieve institutional goals
support external reporting of institutional data (SMA metrics, key performance indicators for governance, international rankings, data exchanges with peer institutions)

Under the general direction of the Assistant Director, Business Intelligence & Data Engineering, the Data Engineering Lead will deliver and manage institutional data pipelines to support the analytics needs of the University of Toronto. This role will translate requirements into operable solutions that align with the overall data architecture, implement and test data pipelines, while delivering documentation, support, and maintenance to users. Ongoing oversight and change management of pipelines will be managed as part of this service, while integrating the appropriate governance approaches and best practices.

The role will help implement new tools and technologies as the University undergoes its platform migration from on-premise to a cloud-based platform. The Lead will not only oversee development processes for institutional data sets but will support teams across the University as we onboard them to the new platform. This role will also track the performance of our resources and related capabilities, while seeking to evolve and scale this service based on the needs of the University.

The role will require general analysis skills, working with clients across shared services and academic divisions including the Compensation and Labour Relations units in Human Resources, Research Services, Enrolment Services, and University Relations to determine information requirements; developing ETL programs for analytics initiatives, leading small projects; and providing technical leadership for data engineering solutions.

The Lead must keep abreast of current tools/technologies including Informatica, SQL Service, Azure Data Factory, Databricks, Azure Databricks etc. The Lead will also have knowledge regarding data architecture, data modeling and data warehouse design. The incumbent will proactively gather material from appropriate web sites, technical publications, white papers, etc. of interest to the department. The incumbent will provide the “hands-on” technical expertise required to implement and maintain data pipeline solutions. Although this expertise is primarily related to ETL, it is not limited to these technologies, and may extend to other development tool sets.

Qualifications Required:

EDUCATION:

Undergraduate degree in computer science or an equivalent combination of education and experience.

EXPERIENCE:

Minimum five (5) years’ experience in database engineering. Experience in managing large scale data warehouse environments. Demonstrable understanding of analysis and design methodologies using appropriate tools. Minimum two (2) years’ experience developing data engineering pipelines. Direct experience with Informatica and Microsoft Azure Platform is highly desirable. Experience in machine learning desirable.

SKILLS:

Proficiency with ETL tools including Informatica; Familiarity with Microsoft Azure Knowledge of AMS systems: FIS and HRIS; Knowledge of student system: ROSI Expert knowledge of MS Excel.

OTHER:

Excellent writing, communication and presentation skills; Strong analytical, problem-solving and interpersonal skills; Understanding of University financial and enrolment matters; Ability to work to strict deadlines and pressure situations; Commitment to diversity and equity.

NOTE: This position is 70% onsite.

Closing Date: 11/25/2026, 11:59PM ET
Employee Group: Salaried
Personnel Subarea:PM
Appointment Type: Budget - Continuing
Schedule: Full-Time
Pay Scale Group & Hiring Zone: PM 3 -- Hiring Zone: $97,336 - $113,558 -- Broadband Salary Range: $97,336 - $162,224
Job Category: Information Technology (IT)

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More about this job

Responsibilities

The Data Engineering Lead will manage and deliver institutional data pipelines to support the University's analytics and data strategy. This role involves translating requirements into operable solutions, overseeing development processes, and supporting the migration from on-premise to cloud-based platforms.

Requirements

Candidates must have an undergraduate degree in computer science or equivalent and at least five years of experience in database engineering. Proficiency in ETL tools, specifically Informatica and Microsoft Azure, is highly desirable along with strong analytical and communication skills.

Skills

Data engineering
ETL
Informatica
Microsoft Azure
SQL Service
Azure Data Factory
Databricks
Data warehousing
Data modeling
Business intelligence
Data governance
Analytical skills
Problem-solving
Communication skills
Project leadership
MS Excel

Visa sponsorship

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Keywords

Data Engineering
Institutional Research
Data Governance
ETL
Informatica
Microsoft Azure
Azure Data Factory
Databricks
SQL Service
Data Warehouse
Data Modeling
Business Intelligence
Cloud Migration
Machine Learning
FIS
HRIS
ROSI
MS Excel
Data Pipelines
Analytics
Change Management
Information Technology
Data Strategy
Reporting
Institutional Data

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