What you'll be doing

• 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 including provisioning, upgrades, and production support.
• 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 build platform capabilities for metadata management, discovery, lineage, schema evolution, and data quality in partnership with security and data stakeholders.
• Troubleshoot distributed systems, contribute to production support and incident response, and drive lasting improvements via root-cause analysis, automation, and operational documentation.
• Mentor engineers across teams through design reviews, code reviews, and hands-on collaboration, strengthening engineering practices and encouraging ownership of complex systems.

Requirements

• Extensive experience designing, building, and operating large-scale, data-intensive distributed systems, including technical leadership of multi-team initiatives.
• Experience coordinating with engineering leadership to accelerate team- and organization-wide delivery within existing processes and practices.
• Proven track record of translating data or business strategy into engineering products and technical roadmaps, aligning near-term delivery with long-term platform vision.
• Track record of building and offering managed platform services to other teams, managing provisioning, upgrades, reliability, and support with direct user interaction for requirements and feedback.
• Experience scaling metadata management systems like data catalogs or lineage tracking systems spanning multiple storage and compute technologies.
• Expertise in Java and/or Python with proven ability to deliver high-quality, maintainable production software; 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 experience building batch and stream processing systems at scale, with practical knowledge of state management, replay, backpressure, and delivery guarantees.
• Experience deploying data processing and query technologies such as Flink, Spark, and ClickHouse, with ability to guide platform users on performance and operational trade-offs.
• Experience with multiple storage technologies including object storage, relational or NoSQL databases, and event streaming systems such as Kafka; deep knowledge of open table formats like Iceberg or Delta Lake.
• Extensive experience with data modeling, schema governance, evolution, and serialization formats such as Arrow, Parquet, Protobuf, or Avro.
• Familiarity with building and operating cloud-native data infrastructure, including Kubernetes, workflow orchestration, automated deployment, and production monitoring.
• Excellent written and verbal communication skills to communicate technical visions, explain trade-offs, align stakeholders, and lead across a globally distributed organization.
• Strong technical judgment and problem-solving skills to prioritize competing needs, deliver incrementally in a fast-paced trading environment, and develop other engineers.

Nice to haves

• Experience scaling managed data services across teams with differing workloads, service expectations, and operational constraints.
• Hands-on knowledge of data governance in regulated environments.
• Familiarity with financial datasets and the needs of trading, quantitative research, or back-office users.

Perks and benefits

• Annual base salary range of $200,000 to $275,000 depending on experience and qualifications.
• Eligibility for an annual discretionary bonus.
• Comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance.
• 401k plan with discretionary employer match.
• Short and long-term disability, life and AD&D insurance.
• Health savings accounts and flexible spending accounts.