Data Engineer (2 years term)

Original job posting

The Data Engineer will design, implement, and maintain robust ETL/ELT pipelines to manage and optimize data infrastructure for high-impact research projects. They will also analyze complex system requirements, develop quality control procedures, and provide technical solutions for IT problems.

Job details

Date Posted: 08/27/2026 Req ID: 50015 Faculty/Division: Faculty of Arts & Science Department: Acceleration Consortium Campus: St. George (Downtown Toronto) Position Number: 00057089 Description: About us:The Faculty of Arts & Science is the heart of Canada’s leading university and one of the most comprehensive and diverse academic divisions in the world. The strength of Arts & Science derives from our combined teaching and research excellence in the humanities, sciences and social sciences across 29 departments, seven colleges and 46 interdisciplinary centres, institutes and programs.We can only realize our mission with the dedication and excellence of engaged staff and faculty. The diversity of opportunities and perspectives within the Faculty reflect the local and global landscape and the need for curiosity, innovative thinking and collaboration. At Arts & Science, we take pride in our legacy of innovation and discovery that has changed the way we think about the world.The Acceleration Consortium (AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of academia, industry, and government that leverages the power of artificial intelligence (AI), robotics, materials sciences, and high-throughput chemistry to create self-driving laboratories (SDLs), also called materials acceleration platforms (MAPs). These autonomous labs rapidly design materials and molecules needed for a sustainable, healthy, and resilient future, with applications ranging from renewable energy and consumer electronics to drugs. AC Staff Scientists will advance the infield of AI-driven autonomous discovery and develop the materials and molecules required to address society’s largest challenges, such as climate change, water pollution, and future pandemics.The Acceleration Consortium received a $200M Canadian First Research Excellence Grant for seven years to develop self-driving labs for chemistry and materials, the largest ever grant to a Canadian University.Your opportunity:Reporting to the Executive Director, Acceleration Consortium and working closely with the (Senior) Research Associates, the Data Engineer plays a pivotal role in managing and optimizing our data infrastructure to support these high-impact research projects. The Data Engineer will be responsible for designing, implementing, and maintaining robust ETL/ELT pipelines that ensure the efficient flow of data from various sources to data warehouses and research databases. This is a grant-based 2-year term position that is ending approximately in May 2028, with the possibility of renewal. Your responsibilities will include: Reconciling business requirements with information architecture needs for highly complex system integration Analyzing and optimizing database software Developing and maintaining quality control procedures Analyzing, recommending, and designing highly complex software architecture Designing, testing, and modifying programming code Leading and planning IT projects Analyzing, recommending and designing technical solutions for highly complex IT problems Serving as a resource to others by providing (non-supervisory) job-related guidance Essential Qualifications: Bachelor's Degree (Master's Degree preferred) in Computer Science, Information Technology, Data Engineering, or a related field or acceptable combination of equivalent experience. Minimum five years recent and relevant Data Engineer experience with a strong background in ETL/ELT processes in materials, chemicals, research, and technology industry or related industries with significant research and development. Experience with data pipeline tools and platforms (e.g., Apache Airflow, AWS Glue, Talend, etc.). Proficiency in SQL, Python, and/or other programming languages commonly used in data engineering as well as data transformation tools (e.g. DBT). Solid understanding of database management systems (RDBMS, NoSQL, etc.) and data warehousing solutions (e.g., AWS Redshift, Google BigQuery, Snowflake, Databricks). Familiarity with cloud computing platforms (e.g. AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Strong problem-solving skills and the ability to work in a fast-paced, research-driven environment. Excellent communication skills, with the ability to collaborate effectively with cross-functional teams. Assets (Nonessential): Experience in a research or academic environment, particularly in handling large and complex scientific datasets. Knowledge of data modeling, schema design, and data architecture best practices. Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus. To be successful in this role you will be: Accountable Communicator Efficient Insightful Problem solver Team player This role may be eligible for an Alternative Work Arrangement in accordance with the University of Toronto’s Alternative Work Arrangements Guideline. Closing Date: 09/18/2026, 11:59PM ETEmployee Group: USW Appointment Type: Grant - Term Schedule: Full-TimePay Scale Group & Hiring Zone:USW Pay Band 16 -- $103,367. with an annual step progression to a maximum of $132,188. Pay scale and job class assignment is subject to determination pursuant to the Job Evaluation/Pay Equity Maintenance Protocol. Job Category: Information Technology (IT) Lived Experience StatementCandidates who are members of Indigenous, Black, racialized and 2SLGBTQ+ communities, persons with disabilities, and other equity deserving groups are encouraged to apply, and their lived experience shall be taken into consideration as applicable to the posted position.

What you’ll do

The Data Engineer will design, implement, and maintain robust ETL/ELT pipelines to manage and optimize data infrastructure for high-impact research projects. They will also analyze complex system requirements, develop quality control procedures, and provide technical solutions for IT problems.

Requirements

Candidates must have a Bachelor's degree in a relevant field and at least five years of recent experience in data engineering with a strong background in ETL/ELT processes. Proficiency in SQL, Python, and cloud-based data warehousing solutions is essential for this role.

Listed skills

• Kubernetes · Preferred
• SQL · Preferred
• Docker · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Engineering
• ETL/ELT Pipelines
• SQL
• Python
• Apache Airflow
• AWS Glue
• Talend
• DBT
• RDBMS
• NoSQL
• AWS Redshift
• Google BigQuery
• Snowflake
• Databricks
• Docker
• Kubernetes
• Pipelines
• Curiosity
• Snowflake (Data Warehouse)
• Resilience
• Planning
• Programming Languages
• Research
• Artificial Intelligence
• Amazon Web Services
• Chemistry
• Teaching
• Microsoft Azure
• Business Requirements
• Containerization
• Cloud Computing
• Commercialization
• Communication
• Computer Science
• Computer Programming
• Information Technology
• Data Architecture
• Database Management Systems
• Data Infrastructure
• Extract Transform Load (ETL)
• Data Transformation
• Data Modeling
• Data Visualization
• Data Warehousing
• Database Tuning
• Electronics
• Water Pollution
• Innovation
• Information Architecture
• Problem Solving

Job areas

• Data & Analytics
• Technology
• Science & Research
• Software
• Education
• Data Engineer
• Software Developers
• Database Administrators