Senior Data Engineer, Unified Platform
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. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.
Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.
We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.
The Data Ecosystem team is an important part of DRW’s Unified Platform (UP) organization, building the platform capabilities, managed infrastructure, and metadata management systems that underpin our common query layer and power thousands of batch and streaming pipelines delivering data across DRW.
As a Senior Data Engineer in our Unified Platform organization, you will design, build, and operate the data platform and managed services used by Traders, Quantitative Researchers, and Back-Office personnel. You will own engineering projects and service components, work directly with platform users to solve technical problems, and contribute to metadata management and governance capabilities. This is a hands-on role combining technical design ownership, software development, production support, and mentorship within the broader platform architecture.
Key Responsibilities
- Design, build, and operate managed platform services for data storage, distributed query execution, batch and streaming processing, and workload orchestration.
- Own technical designs and implementation decisions for services and components within the broader platform architecture, and lead their delivery from requirements through deployment and support.
- Automate provisioning, configuration, upgrades, and monitoring for managed services, reducing manual operations and improving consistency across deployments.
- Build and integrate metadata management tools, including data catalogs and lineage tracking, to help users discover datasets and understand their structure, ownership, and dependencies.
- Implement schema governance, data quality checks, access controls, and usage tracking in line with established policies, working with security and data stakeholders on technical requirements.
- Work with users of managed services to diagnose integration and performance issues, clarify technical requirements, and improve the services their workloads depend on.
- Improve the reliability and performance of managed services and shared processing infrastructure through observability, capacity management, and testing. Participate in production support and incident response for these services, resolving root causes and maintaining operational runbooks.
- Deliver platform upgrades and data migrations with appropriate validation and compatibility checks to protect downstream workloads.
- Lead design and code reviews for the services you own, document technical trade-offs, and contribute improvements to architectural patterns shared across the team.
- Mentor less experienced engineers through hands-on collaboration and feedback, promoting maintainable code, automated testing, and sound operational practices.
Required Qualifications
- 7+ years of experience working with modern data technologies and/or building data-intensive distributed systems.
- Expertise in Java and/or Python, with a proven ability to deliver high-quality, maintainable production software, and strong familiarity with SQL, Bash, and Linux environments.
- Experience building and operating managed data or infrastructure services offered to other teams, including operational automation and production support.