Senior Python Engineer

Job Title: Google Cloud Platform Python Engineer

Location: Schaumburg, IL
Work Mode: Hybrid – 3 days/week onsite
Duration: Long-Term Contract

Job Summary

We are looking for a Python Engineer to join a team building backend software and data solutions for intelligent enterprise applications. This is primarily a Software Engineer / Backend Engineer role with exposure to Data Engineering, Automation, Cloud, and basic GenAI.

The ideal candidate will have strong hands-on experience with Python, REST APIs, FastAPI, SQL, automated testing, Docker, CI/CD, and cloud platforms, with Google Cloud Platform preferred.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python.
• Build and integrate REST APIs using FastAPI and related frameworks.
• Develop data ingestion, transformation, and processing pipelines.
• Write efficient SQL queries and work with relational and cloud databases.
• Develop Python scripts for automation and operational workflows.
• Implement automated testing using pytest/unittest.
• Build and deploy containerized applications using Docker.
• Work with CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar tools.
• Develop and support cloud-based applications, preferably on Google Cloud Platform.
• Monitor application performance, logging, and reliability.
• Collaborate with software, data, and cloud engineering teams.
• Support integration of basic GenAI capabilities into enterprise applications.

Must-Have Skills

• Strong hands-on Python development
• REST API development and integration
• FastAPI experience preferred
• Strong SQL skills
• Experience with PostgreSQL, SQL Server, MySQL, or BigQuery
• pytest / unittest and automated testing
• Python scripting and automation
• Strong OOP and software design patterns
• Docker / containerization
• CI/CD – GitHub Actions, GitLab CI, Jenkins, etc.
• Cloud experience – Google Cloud Platform preferred; AWS/Azure acceptable

Preferred / Additional Skills

• Pandas and NumPy
• Microservices architecture
• Async Python
• Data ingestion and transformation
• Data pipelines
• Google BigQuery
• Google Cloud Run
• Logging and monitoring
• API performance testing
• Basic GenAI / LLM exposure