Data Engineer for Retail Credit at RBC

About

Elevate your career at RBC as a Data Engineer focused on Retail Credit. This innovative role combines data engineering and machine learning to enhance underwriting capabilities powered by AI.

As part of Global Functions Technology at RBC, you will collaborate with cross-functional teams to design and implement scalable data pipelines and feature stores. Your expertise in Python, PySpark, and MLOps practices will ensure high-quality data insights and optimize ML models for transformative financial solutions.

Key Responsibilities:

• Develop feature store with integrated data quality and governance
• Design scalable data pipelines for feature extraction and transformation
• Manage data consistency and lineage for regulatory compliance
• Collaborate with data scientists on standardizing feature definitions
• Conduct data preprocessing and feature engineering for model training

Requirements:

• Degree in Computer Science, Engineering, or related field
• Expertise in Python, PySpark, and data engineering frameworks
• Knowledge of Dev Ops practices for CI/CD pipelines
• Excellent problem-solving and analytical skills
• Experience with Agile methodologies like Scrum or Kanban

Drive technical innovation and enhance data solutions at RBC.