Senior Analytics Engineer (SAS to Python Migration)

Dice is the leading career destination for tech experts at every stage of their careers, and they are seeking a Senior Analytics Engineer to support the modernization of analytics and reporting workflows within a Business Informatics organization. This role focuses on translating and enhancing legacy SAS-based analytics into scalable, maintainable Python-based solutions.

Responsibilities:

• Analyze and interpret existing SAS programs, including DATA steps, PROC SQL, and analytical procedures
• Translate SAS-based analytics and transformations into Python using pandas, numpy, and SQL while preserving business logic
• Partner closely with Business Informatics stakeholders to understand reporting intent, metrics, and downstream usage
• Validate converted logic by reconciling outputs, row counts, and aggregations between SAS and Python
• Improve and modernize analytics pipelines by simplifying logic and reducing technical debt
• Collaborate with technology and data platform teams to ensure Python solutions align with enterprise standards
• Document business logic, assumptions, and data transformations for long-term maintainability
• Ensure accuracy and integrity of analytical outputs through thorough validation and testing

Requirements:

• Strong experience with Python for data analysis, including pandas, numpy, and SQL integration
• Working knowledge of SAS, with the ability to confidently read and interpret existing SAS code
• Experience translating or modernizing legacy analytics or reporting logic
• Solid understanding of analytics concepts such as aggregations, joins, time-based logic, and derived metrics
• Experience validating analytical outputs and ensuring data accuracy
• Ability to collaborate with business users and translate analytical requirements into technical solutions
• Experience in healthcare, payer, or regulated data environments
• Familiarity with SAS macros and common PROC workflows
• Exposure to cloud-based analytics platforms or modern data stacks
• Experience supporting Business Intelligence, reporting, or informatics teams
• Background in analytics engineering or data transformation roles