We are seeking an experienced Python Developer with a robust understanding of SAS-based data workflows and deep hands-on expertise in Python. This is a hands-on contributor role (not a leadership position) focused on building, optimizing, and maintaining data processing solutions.
Required Experience & Skills
Core Python Development Several years of professional experience developing production-grade Python code. Strong proficiency with Python data libraries such as pandas, NumPy , and related ecosystems. Comfortable working independently on complex data processing tasks.
Advanced Data Manipulation
Expertise in merging and joining large datasets efficiently using merge(), join(), and related techniques. Strong understanding of data alignment, indexing strategies, and memory-efficient transformations.
Experience handling complex data structures and edge cases during large-scale data integration. Scalability & Performance Experience processing large or out-of-memory datasets , including: Parallel or distributed processing (e.g., multiprocessing, Dask, Spark, or similar).
Performance tuning to replace or improve upon SAS I/O and batch optimizations.
Ability to profile code and identify bottlenecks in data pipelines. Automation & DevOps Experience automating data workflows and jobs using Python. Familiarity with scheduling, CI/CD pipelines, and environment management.
Comfortable working in Linux-based environments and with version control systems (e.g., Git). Testing & Validation Strong understanding of testing strategies for data and analytics code.
Experience writing unit tests, integration tests, and validation checks to ensure data accuracy and consistency. Ability to validate Python-based outputs against legacy SAS results when required. Hands-on experience working in Jupyter Notebooks for development, analysis, and documentation.
Ability to write clear, reproducible notebooks that communicate logic and results effectively. Nice to Have Prior experience translating or modernizing SAS workflows into Python-based solutions. Exposure to cloud platforms or distributed data environments.