Senior Derived Data Engineer – Market Data & Analytics

P2P; New York (NY); On-site; USD 200,000 - 250,000; Full time

Benefits offered by this job

Discretionary bonus eligibility

Medical, dental, vision insurance

Retirement plan with employer match

Paid vacation and holidays

Job summary

Jump Trading Group is seeking an experienced software engineer to build and maintain the Derived Data platform. You will work with market data to generate bars, residuals, curves, and greeks, collaborating with traders and researchers to fit analytics into real-world workflows.

The role emphasizes scalable systems, streaming data, and clear documentation, with opportunities to expand technical breadth and impact across teams in a fast-paced financial research environment.

Qualifications

• 7+ years of software engineering experience with Python, Rust, and C++.
• 5+ years calculating derived data or consuming it on a team.
• Direct experience calculating bars and residuals from market data (streaming, colocated).
• Strong understanding of trading and research workflows.
• Strong unit-testing / test-driven coding style.
• Experience with various data storage formats and event queues.
• Hands-on Linux experience.
• Willingness to diversify and learn new skills.
• Excellent written and verbal communication.

Responsibilities

• Build and maintain systems that calculate bars and residuals from market data, including streaming data.
• Design scalable, centralized data representations for multiple consumers.
• Collaborate with trading and research teams to fit analytics into workflows.
• Extend analytics to curves, volatility surfaces, and greeks.
• Document solutions and calculations in clear, non-technical terms.

Skills

Python

Rust

C++

Derived data

Linux

Unit testing

Data streaming

Communication

Job description

Jump Trading Group is seeking an experienced software engineer to build and maintain the Derived Data platform. You will work with market data to generate bars, residuals, curves, and greeks, collaborating with traders and researchers to fit analytics into real-world workflows.

The role emphasizes scalable systems, streaming data, and clear documentation, with opportunities to expand technical breadth and impact across teams in a fast-paced financial research environment.