Python Developer - (Systems Modernization)

Katmai

6d•Remote

About The Position

Lead the modernization of core data processing systems. Responsible for translating complex legacy SAS logic into robust, high-performance Python solutions. Build and maintain scalable data pipelines that handle large-scale datasets, ensuring that our data products are accurate, well-documented, and optimized for a cloud-native environment. Work with DSD IT Specialists in an integrated team environment.

Requirements

Ability to read and interpret SAS code.
Experience with Parquet, SQL, JSON, and larger-than-memory datasets.
Experience with libraries like PySpark, multiprocessing, Dask, and code profiling tools.
Experience in Linux environments and cloud-native resources (e.g., AWS).
Strong SQL skills, specifically with PostgreSQL integration.
Version control (Git), unit testing, and technical documentation.
Experience using Python to read and reformat large data files.
Experience improving code performance, including profiling and refactoring code to identify bottlenecks and overhead, preferably in production environments.
Experience writing high-quality code that is well-documented and easy to read, use, maintain, and extend.
Ability to perform basic Linux commands as an end user.
Experience in data validation in a statistical processing environment.
Must pass the Census Bureau Security Investigation / background investigation.
Must obtain and maintain any necessary security access and/or background checks.

Nice To Haves

Five (5) to seven (7) years of related experience with back-end and front-end development, relational database and developing applications or equivalent combination of experience.
Bachelor’s degree in computer science or related field is preferred.
Experience in cloud computing, preferably with Amazon Web Services (AWS), is a plus.
Statistical Analysis System (SAS) programming experience is a plus.

Responsibilities

Analyze existing SAS-based systems and re-implement logic in Python, ensuring functional parity while improving maintainability, scalability, and performance.
Design and develop end-to-end data pipelines to ingest, clean, validate, and transform diverse data formats—including SAS datasets, Parquet, JSON, and SQL—using larger-than-memory processing techniques.
Profile, optimize, and refactor code to eliminate bottlenecks and improve performance. Implement parallel computing strategies using libraries such as Dask and multiprocessing to efficiently process production-scale workloads.
Develop Python solutions that interface with PostgreSQL for high-volume data storage, retrieval, and processing.
Implement automated testing, data validation, and quality assurance processes to ensure the integrity, accuracy, and reliability of critical data assets throughout the data lifecycle.
Maintain high standards for code quality by producing well-documented, readable, maintainable, and extensible code. Participate in peer reviews and knowledge sharing to promote engineering best practices.
Collaborate with DSD IT Specialists and other stakeholders to implement efficient, scalable Python solutions that meet functional and technical requirements.
Partner with DSD stakeholders to validate business and technical requirements, troubleshoot implementation issues, and support the successful modernization of legacy systems.
Attend branch meetings and communicate technical concepts, project updates, and recommendations clearly and effectively.
Maintain regular communication with the team as required.
Maintain regular and punctual attendance.
Perform other duties as assigned.