Archived listing. The details below describe a past opening.
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.
