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TransMarket Group

Junior Data Engineer

Chicago, Illinois, United Statesfull-timeentryAdded today

About this role

TransMarket Group, a Chicago-based proprietary trading firm, seeks a Junior Data Engineer to design and maintain production data systems that power trading operations and business intelligence. You'll work alongside senior engineers to build robust pipelines, databases, and tools using Python, SQL, and modern data infrastructure while gaining hands-on experience in high-performance financial systems.

What you'll do

  • Develop and maintain production-quality data pipelines and services for proprietary trading operations
  • Design and support databases and data models aligned with business requirements
  • Collaborate with traders, software developers, and finance teams to deliver actionable data
  • Learn and apply data engineering best practices under senior developer mentorship
  • Ensure data accuracy, reliability, and timeliness across the firm
  • Build tools and automation to support trading, research, and operational reporting

What they're looking for

  • Python
  • SQL and relational database design
  • Linux environment
  • Git version control
  • RESTful API design
  • Docker and containerization
  • Data pipeline development
  • Data modeling

Benefits

  • Generous profit-sharing program tied to company growth
  • World-class benefits package for full-time employees
  • Family coverage included
  • Hands-on learning and high degree of ownership
  • Exposure to cutting-edge financial technology
  • Collaborative, entrepreneurial culture
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TransMarket Group

TransMarket Group builds high-performance trading infrastructure and low-latency trading systems for financial markets. The company is hiring Network Engineers, Software Engineers, Infrastructure Engineers, and DevOps/SRE professionals to design, maintain, and optimize its trading technology platform.

View all jobs at TransMarket Group

Likely interview questions

  • Walk us through a data pipeline you've built—what were the key challenges and how did you ensure data quality?
  • How would you design a database schema to handle high-volume trading data that needs to be queried in real-time?