Staff Data Engineer - TS/SCI Cleared

Twenty
Arlington, VAPosted 27 March 2026

Job Description

Staff Data Engineer - TS/SCI Cleared ABOUT THE COMPANY At Twenty, we're taking on one of the most critical challenges of our time: defending democracies in the digital age. We develop revolutionary technologies that operate at the intersection of the cyber and electromagnetic domains, where the speed of operations exceeds human sensing and complexity transcends conventional boundaries. Our team doesn't just solve problems – we deliver game-changing outcomes that directly impact national security. We're pragmatic optimists who understand that while our mission of protecting America and its allies is challenging, success is possible. ROLE SUMMARY You will own the data infrastructure that powers Twenty’s cyber operations applications and capabilities. This role is about building a durable, high-performance data lake and the pipelines, schemas, and query patterns that make petabyte-scale datasets usable and economical. You’ll partner closely with engineers and intelligence analysts to turn messy, high-volume operational data into reliable, well-modeled systems that drive real missions. You’ll also lead technical initiatives and mentor other engineers as we scale what we can support and ship. WHO YOU ARE - You think in systems: data modeling, storage formats, compute engines, and access patterns all have to fit together. - You’re opinionated about schema and index design, and you can explain tradeoffs clearly. - You default to measurable reliability: data quality, lineage, repeatability, and operational excellence. - You’re comfortable working with ambiguous datasets and evolving requirements without lowering standards. - You collaborate tightly across roles, especially with engineers and analysts who need fast, correct answers. - You take leadership seriously—mentoring others, raising the bar, and driving initiatives to completion. - You’re motivated by national security outcomes and want your work to matter in the real world. WHAT YOU’LL DO - Lead the development and operation of a data lake for cyber operations and intelligence data. - Design schemas, partitions, and indexes that make complex datasets performant and cost-effective to query. - Partner with engineers and intelligence analysts to define query patterns and data products for mission use cases. - Build and evolve ETL pipelines that are observable, recoverable, and resilient to upstream change. - Drive technical initiatives end-to-end, from architecture decisions through production rollout and iteration. - Establish best practices for data quality, documentation, and operational ownership across the platform. - Mentor engineers on data modeling, performance tuning, and production-grade pipeline design. - Identify bottlenecks in storage/compute/query layers and ship improvements with clear performance wins. MUST HAVE - You have 8+ years of experience in data engineering and/or data architecture. - You have mastery-level expertise building ETL pipelines and operating them in production. - You have deep experience with data lake architecture and systems used to query data lakes. - You have strong schema and index design skills, including partitioning, indexing, and clustering strategies. - You have experience with column-oriented databases in production environments. - You have built data systems from scratch (not only maintained existing platforms). - You have proven leadership experience mentoring engineers and driving technical initiatives. - You are a U.S. citizen and can meet the role’s security requirements. NICE TO HAVE - You have experience with key-value datastores. - You have worked with streaming and message queue systems. - You have experience with graph database technologies. - You have worked with internet/networking datasets (e.g., scan data, DNS, netflow, certificates). - You have experience supporting analysts or operational users with high-stakes data needs. TECH ENVIRONMENT (YOU MIGHT WORK WITH) - Data lakes: Apache ... (truncated, view full listing at source)
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