Responsibilities
- Design real-time distributed trading systems that place orders across a global set of markets and asset classes (Go / C++)
- Build and optimize large-scale data infrastructure and stream processing systems for historical and real-time machine learning feature pipelines (Python/Airflow/Go/beam)
- Own observability and remediation tooling used to analyze trading performance and risk (Go / Python / React)
- Integrate with new assets and markets and drive clarity on the resulting requirements
- Improve the resilience and performance of our trading systems
- Develop tooling to integrate data from diverse vendors, unifying symbol mappings for data consistency
- Lead company spanning complex projects. Collaborate across research, legal, trading, finance operations data, and infra teams to deliver end-to-end trading systems
- Mentor and develop other engineers on the team, and share your practices and knowledge with the team and company
Requirements
- Computer Science Degree or equivalent experience
- 5+ years of software engineering experience building high-performance systems
- Experience operating and scaling mission-critical, large-scale production systems in languages such as Python, Go and C++
- Excellent communication and project management skills in complex technical domains
- Track record mentoring engineers and leading technical direction
Preferred Qualifications
- Expertise in building and optimizing data pipelines (e.g., Apache Airflow, Spark, Kafka)
- Experience with profiling and performance optimizations on distributed systems. (Go / C++)
- Exposure to modern Python data science tooling. (pandas, polars, dask, duckdb etc)
