Top Senior Python Jobs in Chicago, IL

Lead Software Engineer responsible for designing, developing, testing, and maintaining a distributed processing application using Python and Java. Collaborate with product owners, data coaches, analysts, DBAs, and Agile teams to meet backend/frontend requirements, implement cloud and big-data solutions (Spark/Hadoop), and ensure program standards and reliable delivery.

Develop, test, and maintain a complex distributed processing application using Python and Java. Collaborate with product owners, data coaches, analysts, DBAs, and Agile teams to meet backend/frontend requirements. Work with distributed workloads (Spark/Hadoop), SQL/Snowflake, AWS, shell scripting, and job scheduling/process automation. Support delivery under Agile/SAFe practices and ensure alignment with program standards.

Lead development of Python-based web applications using Django and FastAPI, architect scalable solutions, and establish technical standards while mentoring developers and optimizing infrastructure.

The Python Engineer will write maintainable Python software, lead technical initiatives, collaborate globally, and contribute to community engagement at Canonical.

Develop and enhance features for EnrollWise, contribute to a scalable software architecture, review code, collaborate on design and technical feasibility, and maintain software quality.

Lead design, build, and operate scalable backend services and carrier integrations. Provide technical leadership, mentor engineers, drive architecture and best practices, write and test code, troubleshoot production incidents, and improve monitoring and reliability while collaborating with product and cross-functional teams.

Build and maintain internal Python platform libraries and tooling to improve developer experience. Drive runtime, dependency, testing, delivery, monitoring, and performance optimization for Python services (including GPU-enabled workloads). Collaborate cross-functionally to define an opinionated SDLC, support on-call rotations, and balance modern practices with risk-aware change. Enable scalable, low-latency distributed systems and provide AI/ML-facing platform capabilities.