Staff Engineer, Data Platform

drweng; Chicago (IL); On-site; USD 180,000 - 260,000; Full time

Job summary

DRW in Chicago is seeking a Staff Engineer focused on the Data Platform. You will scale data platforms, translate data strategy into engineering products, and deliver solutions used by Traders, Quant Researchers, and Back-Office teams.

This role blends strategic thinking, architectural leadership, and hands-on development, with mentoring of engineers and driving cross-team initiatives across the data ecosystem.

Qualifications

• Extensive experience designing and operating large-scale data systems.
• Ability to translate data strategy into engineering roadmaps.
• Experience delivering managed platform services across teams.
• Experience scaling metadata management systems (catalogs/lineage).
• Proficiency in Java and/or Python; strong SQL and Linux knowledge.
• Deep understanding of distributed systems trade-offs.
• Production experience with batch and streaming processing at scale.

Responsibilities

• Contribute to the vision and evolution of DRW's Data Platform.
• Translate business priorities into platform capabilities and roadmaps.
• Design and own managed platform services for storage and computation.
• Lead cross-team delivery and turn ambiguous requirements into designs.
• Drive architecture reviews and document trade-offs.
• Oversee data governance, metadata, quality, and access controls.
• Mentor engineers through design reviews and code reviews.

Skills

Java/Python development

SQL

Linux environments

Distributed systems design

Architectural leadership

Mentorship

Stakeholder communication

Tools

Data catalogs

Lineage tracking

Job description

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.

Our Unified Platform (UP) organization builds and offers managed data services, shared infrastructure, and metadata management systems that underpin our common query layer and power batch and streaming pipelines that power teams across DRW.

As a Staff Engineer focused on the Data Platform , you will bring experience scaling data platforms to shape and uphold DRW's long-term data platform vision, translating data strategy into engineering products and managed services used by Traders, Quantitative Researchers, and Back-Office personnel. You will work across tooling, producer, and consumer teams to connect business priorities with technical direction and hands‑on delivery. This is an individual contributor role combining strategic thinking, architectural leadership, software development, and mentorship, with responsibility for technical initiatives that span teams.

Key Responsibilities

• Contribute to and uphold the overall vision for DRW's Data Platform, guiding its architecture and evolution to advance the firm's data strategy.
• Work with engineering leads , product managers , and stakeholders to understand business priorities and translate data strategy into engineering products, platform capabilities, and contribute to the sequenced technical roadmap.
• Design , guide, and build managed platform services for data storage, distributed query execution, batch and streaming processing, and workload orchestration, owning their lifecycle from provisioning and upgrades through production support , refining the managed offers from direct user feedback.
• Lead delivery across team boundaries, turning ambiguous requirements into practical designs and measurable outcomes while balancing immediate business needs with long‑term platform goals.
• Drive architecture reviews and technology decisions, documenting trade‑offs and building consensus around patterns that uphold the platform vision across the data ecosystem.
• Own the strategy for large‑scale data governance and b uild platform capabilities for metadata management, discovery, lineage, schema evolution, and data qua lity. Partner with security and data stakeholders on access controls and usage tra cking.
• Troubleshoot distributed systems, contribute to production support and incident response, and drive lasting improvements through root‑cause analysis, automation, and operational documentation.
• Mentor engineers across teams through design reviews, code reviews, and hands‑on collaboration, strengthening engineering practices and helping others take ownership of complex systems.

Required Qualifications

• Extensive experience designing, building, and operating large‑scale, data‑intensive distributed systems , including technical leadership of initiatives spanning multiple teams.
• Experience coordinating with engineering leadership to accelerate team- and organization‑wide delivery within existing processes and practices.
• A track record of translating data or business strategy into engineering products and technical roadmaps, with the judgment to align near‑term delivery with a long‑term platform vision.
• A track record of building and offering managed platform services to other teams, owning provisioning, upgrades, reliability, and ongoing support throughout the service lifecycle , working directly with users to incorporate their requirements and feedback into product and roadmap decisions.
• Experience scaling metadata management systems, such as data catalogs or lineage tracking systems , that span multiple storage and compute technologies .
• Expertise in Java and/ or Python, with a proven ability to deliver high‑quality, maintainable production software, and strong familiarity with SQL and Linux environments.
• Deep understanding of distributed systems trade‑offs, including consistency, fault tolerance, concurrency, partitioning, and recovery from partial failures.
• Production e xperience building both batch and stream processing systems at scale , demonstrating practical knowledge of state management, replay, backpressure, and delivery