Hiring: SAS / Python Data Analyst
Location: Greater Toronto Area
Role Type: Contract

We are looking for a SAS / Python Data Analyst to join a data-focused team supporting analytics, reporting, and modernization initiatives. The ideal candidate will have strong experience working with SAS and SQL, along with hands-on Python experience and the ability to translate existing SAS logic and data processes into modern Python/SQL solutions.
🔹 Key Responsibilities
Develop, execute, and maintain SAS programs, data steps, and PROC SQL for data analysis and reporting.
Analyze and manipulate large datasets using SQL and Python.
Support modernization initiatives involving the migration or re-engineering of existing SAS workloads into Python/SQL.
Develop Python-based data processing solutions using libraries such as pandas and NumPy.
Perform complex joins, transformations, aggregations, data cleansing, and reconciliation.
Validate Python/SQL outputs against existing SAS results to ensure data accuracy and business-rule consistency.
Troubleshoot and optimize data processing workflows for performance and scalability.
Work with business and technical stakeholders to understand requirements and translate them into data solutions.
Perform data quality checks, testing, reconciliation, and production support.
Document data processes, mappings, business rules, and technical solutions.
🔹 Required Skills & Experience
5+ years of hands-on SAS experience, preferably with SAS Base, SAS Enterprise Guide (EG), or SAS Data Integration.
Strong SQL skills, including complex queries, joins, CTEs, aggregations, and data transformations.
Hands-on experience with Python, particularly for data analysis and manipulation.
Experience with pandas and/or NumPy is highly desirable.
Understanding of SAS Data Steps and PROC SQL.
Ability to understand existing SAS scripts and translate/re-engineer logic into Python and SQL.
Strong data analysis, data validation, and troubleshooting skills.
Experience working with large datasets and optimizing data processing.
Strong communication skills and ability to work with both technical and business stakeholders.
🔹 Nice to Have
Experience with SAS-to-Python migration or SAS modernization initiatives.
Experience in banking, financial services, insurance, or other highly regulated environments.
Experience with Teradata, SQL Server, Oracle, or other enterprise databases.
Experience with Jupyter Notebooks.
Experience with ETL/data integration processes.
Exposure to cloud data platforms such as AWS, Azure, or GCP.

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