Senior Software Engineer, Mid-Frequency Platform, UP Reference Data Team

Chicagosenior

OtherSoftware EngineerSoftware Engineering

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Quick Summary

Overview

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world.

Technical Tools

OtherSoftware EngineerSoftware Engineering

Responsibilities

~1 min read

→Build and evolve data and platform capabilities that support mid-frequency trading research workflows
→Partner closely with internal customers to understand their needs and build intuitive self-service tools
→Develop software for large scale data acquisition, storage, accessibility, and visualization
→Design and operate scalable pipelines and platforms using modern "big data" and lakehouse patterns
→Improve reliability, observability, performance, and ergonomics across platform services
→Learn about market microstructure, financial instruments, and markets in which DRW participates or wants to participate in

Are motivated to solve hard problems with deceptively simple solutions
Think a lot about user experience and try to really understand end users’ jobs and pain points
Think a lot about APIs, modular design and testing
Love refactoring and keep trying until you find a better answer
Enjoy making the “right way to do it” the path of least resistance
Have made a random tool for yourself…and then peers ask for it…then other teams ask for it…
Are fiercely proud of your project’s reliability, performance and ease of maintenance

Requirements

~1 min read

5+ years of platform-level software development experience
Strong computer science fundamentals; a degree in Computer Science or equivalent work experience
Financial market & reference data familiarity — understanding instrument IDs, feed normalization etc.
Experience building research platforms and/or supporting mid-frequency trading environments
Comfort working within a globally-distributed team
A background in some of the following a bonus:

Big data technologies: Spark, Delta Lake, Iceberg, Kafka, Airflow and/or Argo Workflows
SQL and data warehousing/lake querying patterns
Cloud-native deployments: AWS, Docker, Kubernetes
Observability: Splunk, Prometheus, Grafana, Sentry