Connect machine learning and BI through Python, SQL, and contemporary data platforms at RBC Wealth Management’s Toronto-based Data & AI organization.

As a Machine Learning Data Engineer, you will support the full ML data lifecycle across global Wealth Management businesses. The work includes feature engineering, training data preparation, model integration, and scalable pipeline development. You will also translate stakeholder requirements into engineering solutions for reporting, dashboards, analytics, and AI.

Key Responsibilities:
Design scalable pipelines for structured and unstructured data
Prepare datasets and features for AI/ML scientists
Support model deployment, monitoring, and continuous improvement
Translate business requirements into robust engineering solutions




Implement data quality testing and observability frameworks

Requirements:
Five-plus years of qualified ML data engineering experience
Python and SQL programming skills at scale
Understanding of warehousing, lakehouse, and data modelling
Experience with DevOps, DataOps, CI/CD, and automated testing
Robust data governance, quality, security, and collaboration skills

Bring machine learning lifecycle knowledge, pipeline expertise, and stakeholder communication skills to RBC’s Wealth Management Data & AI team.
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📌 Machine Learning Data Engineer Rbc Toronto (Canada)
🏢 ODAIA
📍 Canada