Data Engineer

Key Responsibilities

• Build, maintain, and enhance core trading and market data platforms.
• Design and develop scalable data ingestion pipelines for internal and third-party datasets.
• Onboard, normalize, enrich, and curate complex financial datasets.
• Partner closely with traders, quantitative researchers, and developers to support research and production trading workflows.
• Develop data quality, validation, monitoring, and reconciliation frameworks to ensure dataset integrity and accuracy.
• Support the creation and maintenance of historical and point-in-time datasets used in quantitative research and strategy development.
• Improve accessibility and usability of datasets through APIs, tooling, and metadata management.
• Contribute to initiatives involving machine learning, dataset annotation, and AI-driven research workflows.

Required Qualifications

• 3+ years of experience building and supporting production data pipelines.
• Strong Python development skills and experience working within the broader Python data ecosystem.
• Experience designing ingestion workflows for large-scale financial or market data environments.
• Strong understanding of data quality controls, observability, monitoring, and validation processes.
• Experience supporting quantitative research, systematic trading, or investment teams.
• Familiarity with historical, point-in-time, and time-series datasets.

Highly Desired

• Direct experience working with options, futures, or other derivatives datasets.
• Strong understanding of derivatives market structure and associated data models.
• Experience with options chains, futures data, volatility surfaces, Greeks, pricing, or related analytics.
• Experience working with tick data, order book data, market microstructure, or high-volume trading datasets.
• Knowledge of financial data vendors, exchange feeds, and market data onboarding.
• Experience supporting trading desks, quantitative researchers, or systematic investment strategies.