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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Engineer, Data Platform - **Company:** D R W Inc - **Location:** New York, NY, United States - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Big Data, Code Review, Data as a Services, Data Governance, Data Infrastructure, Serialization, Distributed Systems, Fault Tolerance, Protocol Buffers, Python (Programming Language), Linux System Administration, Meta-Data Management, Metadata Repositories, NoSQL, Cloud Services, SQL Databases, Workflow Management Systems, Parquet, Data Processing, Data Storage Technologies, Apache Spark, Data Strategy, Data Lakes, Kubernetes, Storage Technologies, Data Lineage, Apache Flink, Deployment Automation, Avro, Apache Kafka, Vertica, Stream Processing - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25197_84db0740c8de35cd92d4ebd5308db246-2380592202 ## About the Role * 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 guarantees. * Experience deploying data processing and query technologies such as Flink, Spark, and ClickHouse , and the ability to guide platform us ers on the performance and operational trade-offs among them. * Experience with multiple storage technologies, including object storage, relational or NoSQL databases, and event streaming systems such as Kafka . In-depth k nowl ed ge of the internals of open table formats such as Iceberg or Delta Lake. * Extensive e xperience with data modeling, schema governance and evolution, and formats and serialization systems 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, with the ability to communicate a technical vision, explain trade-offs, align stakeholders, and lead through influence across a globally distributed organization. * Strong technical judgment and problem-solving skills, with the ability to prioritize competing needs, deliver incrementally in a fast-paced trading environment, and develop other engineers., * Experience scaling managed data services across teams with different 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. ## Description * 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.