DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.
The UP (Unified Platform) consolidates data and technologies into a comprehensive solution, accelerating time to market. Optimizing decision-making and research, our platform simplifies implementing new ideas, enhancing our competitive edge. UP - Compliance (UP - CMP) is composed of two sub-teams representing the primary functions in Compliance of Regulatory Reporting and Surveillance.
As a Senior Software Engineer in Compliance, you will:
- Build systems with a constant focus on testing, reliability, scalability, and maintainability.
- Collaborate thoughtfully by working in the open with your teammates and end users.
- Work on legacy code as well as green field development.
- Consistently learn by leveraging your time to understand the business needs clearly.
- Learn and promote new technologies with a focus on best practices.
Desirable Experience:
- Multiple years of server-side development.
- Solid understanding of trading fundamentals – prior experience in Physical Energy Trading, Crypto Trading or other non-traditional financial assets a plus.
- Good understanding of functional paradigms and type theory.
- Confident JVM knowledge.
- Modern Java, Scala, and JavaScript knowledge.
- Experience with Airflow or other Python-based workflow orchestration tools.
- Proficiency in domain-driven design and domain modeling.
- Exposure to Kubernetes, Docker, Linux, & git.
- Working knowledge of SQL & Spark.
- Data Lakehouse implementation experience or working knowledge of underlying concepts.
- Experience in a rigorous and results-oriented software engineering team.
This role offers a particularly strong opportunity for a Software Engineer interested in consistent learning, technical growth, and working with large-scale data sets across numerous asset classes, trading venues, and regions globally.