Data Operations Engineer (Usa)

Trexquant is a growing systematic fund manager with a core team of highly accomplished technologists. We are currently seeking an enthusiastic and skilled Data Operations Engineer with a strong operational focus to join our team. As a Data Operations Engineer, you will play a crucial role in monitoring and optimizing our trading processes, enhancing our development and deployment processes, and contributing to the overall efficiency and success of our operations. If you are passionate about optimizing operational workflows, ensuring system reliability, and driving continuous improvement, we encourage you to apply.

Responsibilities:

(1) Operational Monitoring and Troubleshooting:

• Collaborate with teams to establish robust monitoring and alerting systems that provide real-time insights into the trading process status.
• Take a proactive approach to monitoring, promptly identifying and resolving operational issues to minimize downtime and disruptions.

(2) Continuous Integration and Deployment:

• Develop, enhance, and maintain pipelines dedicated to facilitating data/alpha/strategy generation, testing, and deployment procedures.
• Foster close collaboration with research teams to ensure the smooth deployment of scripts, promoting seamless integration of research findings into practical applications.

(3) Quality Control and Assurance:

• Establish and sustain quality control measures to ensure the consistency and robustness of scripts and applications.
• Conduct regular inspections and audits of production lines to identify and rectify any quality-related issues promptly.

(4) Continuous Improvement Initiatives:

• Identify opportunities for continuous improvement within the production process, driven by data analysis and performance metrics.
• Lead or contribute to cross-functional improvement projects aimed at enhancing production efficiency and increasing overall output.

(5) Documentation and Reporting:

• Maintain accurate records of production processes, performance metrics, and quality control data.
• Generate regular reports and provide insights to management on production performance, trends, and improvement initiatives.