Senior Data Engineer
Belvedere Trading is a leading proprietary trading firm and market maker headquartered in Chicago, with additional offices in Boulder, New York, and Singapore. Founded in 2002, the firm builds proprietary trading technology and risk management systems to capitalize on market inefficiencies across options and other derivatives markets.
About Belvedere Trading
Belvedere Trading emerged in March 2002 as one of Chicago's newest market makers, establishing its place in the SPX pit on the floor of the Chicago Board Options Exchange. Since inception, the firm has invested iteratively in proprietary technology, starting with an options model, adapting it to handheld computers, and eventually building its software systems from the ground up. Due to its ultramodern proprietary technology and risk management capabilities, Belvedere is able to quickly capitalize on inefficiencies in the marketplace, with trading models and software systems continually re-engineered, optimized, and maintained to stay competitive. The firm operates from Chicago, Boulder, New York, and Singapore, employs close to 300 individuals, and is known for low turnover, high referral rates, and a strong company culture centered on core values such as teamwork, ownership, and innovation. Belvedere focuses on proprietary trading across asset classes including equity and commodity options, leveraging cutting-edge technology and talented people to sustain its growth.
Skills
About the Role
You'll work directly with our trading desks to improve trading performance, ensuring data availability, breadth, and reliability so better trading decisions can be made. You'll be responsible for data services, including ETL pipeline implementation, data warehouse architecture, data quality automation, and analytic visualization. You'll need minimal guidance on architecture best practices and will communicate clearly to stakeholders across the organization. You'll solve challenging problems arising from petabytes of high-fidelity data, incrementally adding value to the trading desk while designing long-term architectures that scale.
Requirements
- Experience designing and developing big data warehouses and ETL pipelines
- Proven knowledge of SQL and Python
- Demonstrated ability to navigate and integrate data across multiple data platforms, including RDBMS, NoSQL, and Time Series
- Experience with real time messaging systems, such as Kafka, Kinesis, and Pulsar, and with developing a stream processing framework, such as Flink or Spark, a plus
- Proficiency in crafting high-performance BigQuery queries, optimizing for efficiency and scalability to handle large datasets effectively
- Excellent verbal and written communication, analytical, and problem-solving skills
Responsibilities
- Work with traders to understand analytic needs to improve trading performance
- Design and maintain a modular data architecture to facilitate and scale future analysis
- Ensure high data quality for all analytical trading datasets
- Hold other team members to data standards, including modular design, testing, and documentation
- Hold other team members to visual standards, including modular design, testing, and documentation
- Ensure technical solutions are simple and scale well for future use cases