SAS / Python Developer

SAS / Python Developer - T4 only Location: Toronto ON (Hybrid - 3 Days/Week) Primary Skills SAS, Python, Migration

Primary Experience 7+ years of Experience in SAS, Python

Seeking an experienced

SAS / Python Developer to join data modernization and migration team. In this role, you will be responsible for analyzing, converting, optimizing, and modernizing legacy SAS-based analytical workflows, data steps, macros, and reports into scalable, production-ready Python environments. You will work closely with data architects, business stakeholders, and infrastructure teams to ensure code accuracy and parity during the transition.

Key Responsibilities

Key ResponsibilitiesCode Migration & Translation:

Interpret and convert legacy SAS programs (including Base SAS, DATA steps, SAS macros, and PROC SQL) into modular, efficient

Python scripts.

Data Processing & Pipelines:

Build, maintain, and optimize data ingestion, transformation, and processing pipelines using

Python data manipulation libraries (pandas, NumPy) and SQL.

Validation & Testing:

Perform side-by-side output validation and debugging between legacy SAS outputs and new

Python implementations to ensure statistical and logical parity.

Automation & Infrastructure:

Support Unix/Linux-based automation, schedule jobs via CRON or enterprise orchestrators, and work within containerized or cloud-based Anaconda/JupyterHub environments.

Code Quality & Documentation:

Maintain clean version control using Git/GitHub, write unit tests, and produce thorough technical documentation for migrated pipelines.

Required Qualifications

Required QualificationsEducation

Bachelor's or master's degree in computer science, Data Engineering, Statistics, or a related quantitative field.

SAS Experience

3+ years of hands-on development with Base SAS, SAS Macros, and PROC SQL.

Python Experience

2+ years of production Python development, with strong proficiency in pandas, data wrangling, and relational SQL.

Environment & Tools:

Experience working in Anaconda environments, Git/GitHub, and Linux/Unix shell scripting.

Analytical Skills

Strong debugging, root-cause analysis, and side-by-side data validation capabilities.