Staff Engineer, Data Platform

In this Staff Engineer role, you shape DRW’s Data Platform to enable scalable data usage across traders, researchers, and back-office teams. You will translate data strategy into maintainable engineering products and managed services, guiding cross-team delivery and platform evolution. You’ll tackle governance, metadata, and distribution challenges, balancing immediate needs with a long-term vision. This is a hands-on, architectural leadership position that drives impact through scalable data systems and collaboration. You’ll work with a global, high-expectation team that values integrity, innovation, and execution.

• group medical
• pharmacy
• dental and vision insurance
• 401k with discretionary employer match
• short and long-term disability
• life and AD&D insurance

• Contribute to and uphold the vision for DRW’s Data Platform and guide its architecture
• Translate business priorities into engineering products and a sequenced technical roadmap
• Design and build managed platform services for data storage, query execution, batch/stream processing, and workload orchestration
• Lead cross-team delivery, turning ambiguous requirements into practical designs with measurable outcomes
• Drive architecture reviews, document trade-offs, and build consensus across the data ecosystem
• Own data governance strategy and platform capabilities for metadata management, lineage, schema evolution, and data quality, partnering on security and access controls
• Troubleshoot distributed systems, contribute to production support and incident response, and drive improvements through automation
• Mentor engineers through design/code reviews and hands-on collaboration

• Extensive experience designing, building, and operating large-scale, data-intensive distributed systems
• Experience coordinating with engineering leadership to accelerate delivery
• Track record translating data or business strategy into engineering products and roadmaps
• Experience building managed platform services with provisioning, upgrades, reliability, and user feedback into roadmaps
• Experience scaling metadata management systems across multiple storage/compute technologies
• Expertise in Java and/or Python; strong SQL and Linux familiarity
• Deep understanding of distributed systems trade-offs (consistency, fault tolerance, concurrency, partitioning)
• Production experience with batch and streaming at scale (state management, replay, backpressure, delivery guarantees)
• Experience deploying Flink, Spark, and ClickHouse and guiding users on trade-offs
• Experience with storage technologies (object storage, relational/NoSQL, Kafka) and open table formats (Iceberg/Delta Lake)
• Data modeling, schema governance/evolution; formats like Arrow, Parquet, Protobuf, Avro
• Cloud-native data infrastructure including Kubernetes, workflow orchestration, automated deployment, monitoring
• Excellent communication, leadership through influence across a global org
• Strong technical judgment and ability to mentor others

• Communication
• Leadership
• Problem-solving
• Java
• Python
• SQL