Key Responsibilities

• Design, implement, and maintain components of our data platform, with a strong focus on data onboarding and automation.
• Build and optimize data ingestion pipelines that clean, transform, and load large volumes of structured and unstructured data.
• Develop automated data processing, transformation, and quality assurance workflows to ensure completeness, accuracy, and reliability.
• Write and manage distributed data pipelines supporting both real-time and batch processing across cloud environments.
• Champion a collaborative code review culture that promotes maintainability, best practices, and continuous improvement.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 10+ years of professional experience in software or data engineering.
• Proficiency in Python (required), with working knowledge of SQL and Spark/PySpark.
• Hands-on experience with cloud platforms and data tools, including distributed data pipeline development and orchestration.
• Strong written and verbal communication skills in English, with the ability to document clearly and concisely.

Preferred Qualifications

• Experience building and integrating AI tools into data engineering workflows.
• Data engineering certification (e.g., Databricks Certified Data Engineering Associate or Professional).
• Prior experience in fintech, capital markets, or a regulated data environment.

This position will be located in Toronto, Canada, and offers the opportunity for a hybrid work environment at least 3 days a week in-office, subject to change, providing flexibility and accessibility for qualified candidates.