Data Engineer (2 years term)

University of Toronto•Toronto, ON

2d•Onsite

About The Position

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. 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.

Requirements

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.

Nice To Haves

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.

Responsibilities

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