Python Developer

Python Developer (SAS Background Preferred)

We are seeking an experienced Python Developer with a strong 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.

• Several years of professional experience developing production‑grade Python code.
• Strong proficiency with Python data libraries such as pandas, Num Py
  , and related ecosystems.
• Comfortable working independently on complex data processing tasks.

• 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.

• 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.

• 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).

• 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.

• Prior experience translating or modernizing SAS workflows into Python‑based solutions.
• Exposure to cloud platforms or distributed data environments.