Python Data Engineer

Role: Data Platform Engineer (Python/SQL/SAS/AWS S3/Copilot or LLM Tools)

Location: Toronto - Hybrid (4 Days WFO)

Hiring Mode: Contract (12 months with possibility of Extension)

Industry: Banking/Investment Banking/Financial Industry Only

Pay: CAD 60/Hr.

Role Descriptions

We are seeking a skilled Data Platform Engineer to design and maintain the technical migration framework used in the large-scale conversion of legacy SAS codebases to Python using generative and agentic AI tooling. In this role| you will help architect and maintain a generalized repository structure that can integrate with any SAS codebase and establish standardized processes for managing per-project credentials| configurations| and dependencies. You will ensure that AI-generated Python code can reliably connect to and query required databases and dependency libraries| and you will refactor| harden| and document that generated code to meet production standards for performance and readability.You will implement a robust logging and error handling framework to maximize transparency throughout the conversion process and take full ownership of Git repository management for the duration of the project.You will also closely collaborate with a Data Scientist to continuously maintain and evolve the migration framework as new conversion needs and findings emerge.

Required Qualifications

• 1 year of relevant experience in a professional setting
• Proficiency in Python for data engineering (pandas| SQLAlchemy| boto3| PyArrow| or similar)
• Proficiency in SQL and interacting with data stored in remotecloud infrastructure (e.g.| AWS S3| any SQL DBMS| or similar)
• Proficiency in SQL query optimization for interacting with large datasets
• Experience interacting with various data formats including Parquet| CSV| JSON| etc.
• Proficiency in collaborative version control with Git
• Experience using agentic coding assistants or LLM-based tools (e.g.| Claude Code| GitHub Copilot) in a professional setting

Preferred Qualifications

• Background in regulated or enterprise environments where SAS is commonly used (pharma| finance| insurance| government)
• Experience working in a UNIX environment
• Familiarity with credit risk models (PD| EAD| LGD) and IFRS9 regulatory requirements
• Basic knowledge of SAS sufficient to read and interpret existing code (SAS proficiency not required)
• Experience building or refactoring data pipelines in Python
• Experience in large-scale code migration or modernization projects

Key Responsibilities

• Create a generalized repository structure for code conversions to occur that can integrate with any SAS codebase| e.g. processes for managing per-project credentials| configurations| and dependencies
• Ensure that generated Python files can reliably connect to and query any databases and dependency libraries necessary for execution
• Refactor| harden| and document AI generated Python code for performance| readability| to meet production standards
• Implement a logging and error handling framework to maximize transparency during the code conversion process
• Manage and take ownership of Git repositories throughout the projects duration Collaborate closely with a data scientist to maintain and evolve the migration framework based on conversion.