Data Engineer, Lead

at University of Toronto, Toronto, Canada

Listed on EduAtlas: live school vacancies from schools’ own careers pages and public job services. Apply on jobs.utoronto.ca.

Salary

Not given in the advert

Closing date

26 November 2026

Start

Not given in the advert

Type of post

IT and technicians
A support post, not a teaching post.

First seen

4 November 2026, on a public job listing

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The advert

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)

About University of Toronto

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