Data Engineer, Python and PySpark with SQL & SAS

About

This role supports the bank’s credit strategy modernization by migrating legacy SAS processes to Python and PySpark. The project involves optimizing data processing across HDFS/Hive and AWS S3 platforms to improve scalability, efficiency, and accuracy in credit risk management solutions.

Responsibilities

• Build and optimize scalable data pipelines in Python and PySpark, ensuring reliability and performance across HDFS/Hive and AWS S3 environments.
• Lead migration initiatives transforming legacy SAS processes into modern, cloud-ready Python/PySpark solutions.
• Architect data workflows that support credit risk analytics and business intelligence at scale.
• Write production-grade code with rigorous testing, documentation, and adherence to software engineering best practices.
• Partner with data scientists and stakeholders to translate business requirements into robust technical solutions.
• Manage code quality and collaboration through GitHub version control and peer review processes.
• Document technical infrastructure to enable team knowledge sharing and system maintainability.

Mandatory Skills

• 3+ years hands-on data engineering experience, ideally in financial services or credit risk environments.
• Advanced proficiency in Python and PySpark for designing and optimizing large-scale data processing solutions.
• Strong SQL expertise with demonstrated experience in big data platforms (HDFS, Hive, or equivalent).
• Proven ability to translate complex data requirements into clear, actionable solutions that drive business decisions.
• Software engineering discipline – writes clean, testable, and maintainable code with attention to quality and documentation.

Nice-to-Have Skills

• Track record of solving ambiguous, high-impact problems with clear decision-making and collaborative problem resolution.
• Excellent communication skills – ability to explain technical concepts clearly to both technical and non-technical stakeholders.
• Background in financial services, particularly in credit risk, lending, or regulatory analytics.
• Experience with legacy systems and languages (SAS, TRIAD, BLAZE, or similar mainframe/proprietary platforms) – valuable for understanding existing processes during migration.

Assignment Length

This is a 12-month contract position.

Start Date

ASAP.

Assignment Location

Toronto, Ontario, Canada – Hybrid, 4 days in office.