Data Engineer, Lead

Data Engineer, LeadDate 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
DescriptionThe 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 programsfor analytics initiatives, leading small projects;
and providing technicalleadership 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 RequiredEDUCATIONUndergraduate degree in computer science or an equivalent combination of education and experience.
EXPERIENCEMinimum 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.
SKILLSProficiency 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.
OTHERExcellent 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 diversityand equity.
NOTE: This position is 70% onsiteClosing Date:
11/25/2026, 11:59PM ETEmployee Group:
SalariedPersonnel Subarea:
PMAppointment Type:
Budget - ContinuingSchedule:
Full-TimePay Scale Group & Hiring Zone:
PM 3 -- Hiring Zone: $97,336 - $113,558 -- Broadband Salary Range: $97,336 - $162,224
Diversity StatementThe University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes.For more information, please see
Accessibility StatementThe University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.If you require any accommodations at any point during the application and hiring process, please contact View email address on ca.hrm.tc.
Indigenous Substantiation ProcessThe University of Toronto has implemented a process to substantiate Indigenous Membership/Citizenship/Enrolment for candidates who identify as Indigenous. For more information about this process, please refer to the Indigenous Substantiation Website.
Job Segment: Data Architect, Data Modeler, Computer Science, Data Warehouse, Database, Data, Technology#J-18808-Ljbffr