Data Engineering Specialist (Fintech)

TL;DR

Data Engineering Specialist (Python/Spark): Designing and scaling data infrastructure for a global data marketplace with an accent on data onboarding and automation. Focus on building distributed data pipelines, optimizing ingestion workflows, and ensuring high data quality for financial professionals.

Location: Hybrid in Toronto, Canada (at least 3 days a week in-office)

Salary: $84,000 - $115,000

Company

One of the world's largest data marketplaces serving hundreds of thousands of professionals across finance and technology.

What you will do

• Design and maintain data platform components with a strong focus on data onboarding and automation.
• Build and optimize ingestion pipelines to clean, transform, and load large volumes of structured and unstructured data.
• Develop automated data processing, transformation, and quality assurance workflows.
• Manage distributed data pipelines supporting real-time and batch processing across cloud environments.
• Promote a collaborative code review culture to ensure maintainability and engineering excellence.

Requirements

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 6+ years of professional experience in software or data engineering.
• Proficiency in Python, SQL, and Spark/PySpark.
• Hands-on experience with cloud platforms and distributed data pipeline orchestration.
• Strong written and verbal communication skills in English.

Nice to have

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

Culture & Benefits

• Competitive rewards package including base salary, annual bonus/commission, and equity.
• Comprehensive health and family benefits.
• Opportunities for professional growth in a high-impact, fast-paced environment.
• Hybrid work environment offering flexibility and accessibility.