Data Engineer

Selby Jennings; New York (NY); On-site; USD 110,000 - 180,000; Full time

Job summary

Selby Jennings partners with a leading quantitative trading and investment firm to hire a Data Engineer for a front-office team focused on building and maintaining the datasets powering systematic trading and research.

You will work directly with traders, researchers, and quantitative developers to onboard new datasets, improve data quality, and develop scalable data infrastructure supporting derivatives and other electronic trading strategies.

Qualifications

• 3+ years building and supporting production data pipelines.
• Strong Python development skills in the Python data ecosystem.
• Experience designing ingestion workflows for large-scale financial data.
• 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.

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 with traders, researchers, and developers to support research and production trading workflows.
• Develop data quality, validation, monitoring, and reconciliation frameworks to ensure dataset integrity.
• Support the creation and maintenance of historical and point-in-time datasets used in research.
• 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.

Skills

Python

Data pipelines

Data quality

Observability

Time-series data

APIs

Metadata management

Job description

We are partnering with a leading quantitative trading and investment firm seeking a Data Engineer to join a front-office team focused on building and maintaining the datasets that power systematic trading, quantitative research, and investment decision-making.

This individual will work directly with traders, researchers, and quantitative developers to onboard new datasets, improve data quality, and develop scalable data infrastructure supporting derivatives and other electronic trading strategies. The role offers significant exposure to market data, investment research workflows, and high-impact trading systems.

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 Experience

• 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.