Python Engineer at Jobot Chicago, IL
Listed on 2026-07-15
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Software Development
Python, Unix/Linux
Python Engineer (Chicago, IL)
Python Engineer job WING CHICAGO TRADING COMPANY with Amazing Culture & Benefits.
Salary$130,000 – $200,000 per year.
About the CompanyWe are a growing Trading firm with a product focused mindset centered around our technology and strategies. We create, code, and implement robust trading strategies in the financial markets, staying ahead of the game.
Why Join Us?The ideal hire is an experienced Python developer who knows how to code, understands algorithms, and can follow instructions. The role also requires design, architecture, analysis, and technical documentation skills. We favor generalists who can handle multiple tasks over specialists.
Job DetailsPrior financial market/proprietary trading knowledge is necessary. The hire will assist the lead developer with coding new strategies and system administration tasks such as:
- Server configuration (Ansible)
- Real‑time messaging (RabbitMQ)
- Task management (Airflow)
- Micro services (Docker)
- System auditing
- Deployment automation (Jenkins)
- Log management
- Database management (MongoDB, SQL)
- Python scripting
- Data analysis (Pandas, Scikit‑Learn)
We strongly prefer experience with CentOS (Linux) for remote servers, terminal/bash, crontab, systemd, SSH and SCP, Python 3, Num Py, Tensor Flow, Click, IQfeed, CQG, IB, Trade Station, and especially Rithmic (API).
Responsibilities- Work with the lead developer to code and refine new trading strategies.
- Perform system administration tasks including server configuration, messaging, task orchestration, and monitoring.
- Deploy and maintain micro services and automated pipelines.
- Document design decisions, architecture, and technical specifications.
- Experience in Python development.
- Proficiency with financial markets or proprietary trading systems.
- Hands‑on knowledge of CentOS, Bash, crontab, systemd, SSH, and SCP.
- Familiarity with Ansible, RabbitMQ, Airflow, Docker, Jenkins, Git, MongoDB, SQL, Pandas, Scikit‑Learn, and related tools.
- Comfort with machine learning libraries such as Num Py, Tensor Flow.
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