DRW
Data Engineer, Cumberland/FICCO
About this role
DRW, a global trading firm, seeks a Data Engineer to build and maintain datasets supporting options and fixed income trading strategies. You'll design data pipelines, ensure data quality, and collaborate with traders and researchers to support data-driven decision-making across multiple asset classes.
What you'll do
- Design and implement data ingestion pipelines from internal and vendor sources
- Build, maintain, and manage core trading datasets for options and delta-one strategies
- Develop and execute data quality control processes to detect gaps and inaccuracies
- Collaborate with traders and researchers to apply novel ideas to historical datasets
- Create AI-sympathetic annotations for new and existing datasets
- Monitor data pipeline health with observability and alerting systems
What they're looking for
- Data pipeline design and implementation
- Python data science ecosystem
- Financial data engineering (point-in-time, time-series analysis)
- Options and futures products knowledge
- Data quality and control processes
- Monitoring and observability systems
- Financial data vendor landscape expertise
- Agile and fast-paced environment adaptability
Benefits
- Annual base salary: $150,000–$200,000
- Annual discretionary bonus
- Group medical, pharmacy, dental, and vision insurance
- 401(k) with discretionary employer match
- Short and long-term disability, life, and AD&D insurance
- Health savings accounts and flexible spending accounts
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DRW
DRW is a diversified trading firm that builds and maintains trading technology infrastructure, risk management systems, and systematic trading platforms supporting global 24/7 operations across multiple asset classes. The company is hiring Desktop Systems Engineers, Trade Systems Engineers, and Software Engineers to support endpoint infrastructure, trading system reliability, risk analytics, and full-stack trading platform development.
- Website
- drw.com
Likely interview questions
- Walk us through a data ingestion pipeline you've designed. What challenges did you face with data quality, and how did you address them?
- How would you approach onboarding a new financial data vendor into our system, and what validation steps would you implement?