Data Engineer | Post Trade Analytics
Jump Trading is a global trading firm where traders, engineers, and researchers develop trading strategies, models, infrastructure, and systems across asset classes and time horizons.
About Jump Trading
Jump Trading is a global trading firm focused on research-driven trading and the engineering of scalable models, tools, infrastructure, and execution systems. Its operations combine trading, technology, AI/ML, and quantitative research, and it also runs research and talent programs including conference travel grants and a fellowship program.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will own the datasets and pipelines that support post-trade analytics and trading decisions. You will partner with traders and quantitative researchers to create data products, build and scale ETL and analytics pipelines, implement validation, monitoring, alerting, and lineage frameworks, respond to production incidents, optimize processing for speed and resilience, and develop tools and infrastructure for research and trading teams.
Requirements
- At least 3 years of experience as a data engineer or software engineer working with large-scale data
- Proficiency in Python or C++
- Experience building, operating, and scaling ETL or ELT pipelines
- Experience with orchestration, scheduling, and dependency management
- Strong command of SQL
- Familiarity with Pandas and NumPy
- Analytical and problem-solving abilities
- Curiosity about financial business logic
- Proficiency in Linux environments
- Reliable and predictable availability
Responsibilities
- Partner with traders and quantitative researchers to create data products
- Build and scale datasets and data pipelines
- Support trading strategies and execution quality with data engineering
- Build data validation, monitoring, alerting, and lineage frameworks
- Respond rapidly to pipeline and production incidents
- Optimize data processing and workflows for speed, cost, and resilience
- Develop tools, documentation, and foundational infrastructure