Trading Data Engineer — Build & Quality Pipelines

DRW; Chicago (IL); On-site; USD 150,000 - 200,000; Full time

Job summary

DRW is seeking a Data Engineer to join our trading team in Chicago. You will onboard, transform, and curate datasets to support options and delta-one trading strategies, collaborating with traders, researchers, and quantitative developers.

You will build and maintain core trading datasets, implement data quality controls, and integrate data from internal and vendor sources, while contributing to research initiatives and data annotation efforts.

Qualifications

• 3+ years of experience designing and implementing ingestion pipelines.
• Foundational understanding of the Python data science ecosystem.
• Strong understanding of option and future products and their data requirements.
• Strong understanding of financial point-in-time and time-series data and analysis.
• An understanding of the financial data vendor landscape and product offerings.
• Proven expertise in developing data quality control processes to detect gaps or inaccuracies.
• Experience with monitoring, observability, and alerting systems for data pipelines.
• Proven ability to work in an agile, fast-paced environment and handle trading environment demands.

Responsibilities

• Build, maintain, and manage core trading datasets.
• Implement data quality and control processes.
• Incorporate new data from internally derived and vendor systems.
• Collaborate with research teams to apply ideas to historic data sets.
• Create AI sympathetic annotations to new and existing data sets.

Skills

Ingestion pipelines

Python

Options data

Time-series data

Vendor data

Data quality

Observability

Trading environment

Job description

DRW is seeking a Data Engineer to join our trading team in Chicago. You will onboard, transform, and curate datasets to support options and delta-one trading strategies, collaborating with traders, researchers, and quantitative developers.

You will build and maintain core trading datasets, implement data quality controls, and integrate data from internal and vendor sources, while contributing to research initiatives and data annotation efforts.