Python Developer - TS/SCI w/Poly - Herndon//Chantilly Va.

Job Description

Job Description

Are you a skilled Python Developer passionate about building robust data processing applications? SpatialGIS Services is looking for a talented individual to join our team. In this role, you'll work collaboratively to implement new functionality, while also taking ownership of key aspects of the software development lifecycle.

You'll be instrumental in translating requirements into user stories, designing new features to interface with existing systems and open-source tools, and ensuring code quality through automated testing within our CI/CD pipelines. This position requires strong knowledge of cloud software deployment, including familiarity with parallel processing in Python, large data processing using packages such as PySpark, and optimizing Python code for containerized architectures. If you're ready to make an impact in a fast-paced, innovative environment, we want to hear from you!

Work closely with the Chief Engineer and Technical Leads to translate requirements into user stories and integrate new functionality into various software applications.

Build and implement automated testing frameworks to ensure high code quality and robust CI/CD deployment processes.

Develop web APIs to interface with cloud applications and databases, contributing to cloud-native software applications.

Collaborate effectively as part of an Agile team to deliver software iteratively.

Integrate Python code into Docker containers as part of a distributed architecture.

Design software application components independently based on requirements.

Guide technical design and architecture, ensuring alignment with best practices.

Interface directly with customer stakeholders to align on requirements and technical implementations.

Active TS/SCI w/Polygraph security clearance is required.

Data Processing Python Libraries such as PySpark, Pandas, and Numpy.

API development in Python using libraries such as FastAPI.

Unit Testing Frameworks in PyTest and Mocking.

Experience with Python ORM tools for database as code, such as SQLAlchemy.

Experience deploying containerized Python code using Docker on cloud platforms such as AWS.

Experience using NLP toolkits and frameworks to integrate into production systems.

Experience deploying AI Models into production using Python Libraries and Frameworks.