Junior Data Engineer

Position Details:

Title: Junior Data Engineer

Duration: Full-time, Permanent

Location: Toronto, ON- Hybrid 3x/week in office

Start Date: ASAP

Compensation and Benefits: $80-$90k & Benefits: Standard health, dental, vacation, and personal day package (aligned with firm policy)

Interview Process: 3 Rounds- Virtual and Inperson

• Design, build, and maintain data pipelines that integrate data from multiple sources (Bloomberg, Morningstar, Nasdaq, etc.).


• Support production systems, troubleshoot data issues, and automate workflows to increase efficiency.


• Enforce data governance and data quality standards in collaboration with internal stakeholders.


• Partner with data scientists, analysts, and product teams to ensure smooth delivery of data products.


• Participate in code reviews, documentation updates, and continuous improvement initiatives.


• Perform data analysis on structured and unstructured datasets to identify insights and issues.


• Stay current on modern data engineering tools, frameworks, and cloud technologies.

Must-Haves:

• Bachelor s degree or college diploma in Computer Science, Engineering, or related field ideally from University of Waterloo, University of Toronto, or Queen s University


• 2 3 years of hands-on data engineering experience (entry level candidates with strong co-op or project experience will also be considered).



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• Strong programming skills in Python and SQL.


• Hands-on experience with AWS Data & Analytics stack: EMR, Glue, Lake Formation, Airflow, PySpark, Trino, Hudi, Iceberg.


• Understanding of Big Data concepts: change data capture, data quality, and data lineage.


• Familiarity with data governance principles.


• AWS Certified Data & Analytics Specialty (or equivalent).

Nice-to-Haves / Plusses:

• Experience with sustainable investing or ESG datasets.


• Prior experience in financial services, investment management, or capital markets.


• Familiarity with market data vendors (Bloomberg, Capital IQ, S&P, Morningstar).


• Exposure to Scala or additional data engineering frameworks.


• Understanding of enterprise data architecture and governance frameworks.