Twenty-posted 2 months ago
Full-time • Senior
Washington, DC

Twenty is seeking a Senior Data Engineer for an in-office position in its Arlington, VA office to architect and lead the development of data infrastructure that powers our cyber operations applications and capabilities. We're looking for someone with 8+ years of experience in data engineering and architecture, with mastery-level expertise in ETL pipeline development, data lake architecture, and schema design for complex datasets, plus proven leadership experience mentoring engineers and driving technical initiatives. In this role, you'll architect scalable data lakes that aggregate cyber operation data from diverse sources, lead the design of sophisticated graph database schemas that capture relationships across cyber networks, personas, physical world entities, and electromagnetic spectrum data, establish best practices for AI/ML data preparation workflows, and mentor junior data engineers while driving technical excellence across the data platform. You'll join a world-class product and engineering team that delivers mission-critical solutions for U.S. national security, working in both cloud and on-premises environments to build data infrastructure that operates at machine speed. If you're passionate about solving complex data architecture challenges while leading technical initiatives and making a direct impact on national security, we want to talk to you.

  • Lead the design and architecture of enterprise-scale data platforms that support mission-critical cyber operations.
  • Define technical vision and roadmap for data infrastructure, balancing operational needs with scalability and performance.
  • Evaluate and recommend engineering courses of action for data platform enhancements and technology adoption.
  • Drive technical decision-making for complex data architecture challenges across multiple systems and teams.
  • Establish data engineering standards, best practices, and design patterns across the organization.
  • Lead architecture review sessions and provide technical guidance on data-intensive projects.
  • Architect and implement highly scalable, multi-petabyte data lake solutions on AWS to support applications and cyber operations workflows.
  • Design sophisticated data ingestion frameworks that collect and consolidate data from diverse sources.
  • Implement advanced data partitioning, compression, and storage optimization strategies.
  • Establish comprehensive data governance frameworks including data lineage, cataloging, metadata management, and quality monitoring.
  • Design data mesh architectures that enable domain-oriented data ownership while maintaining central governance.
  • Lead capacity planning and cost optimization efforts for petabyte-scale data infrastructure.
  • Architect robust, fault-tolerant ETL pipelines that transform raw cyber operation data into structured formats for analysis at scale.
  • Design complex data validation and quality assurance frameworks.
  • Implement hybrid streaming and batch processing architectures.
  • Lead development of sophisticated data enrichment processes.
  • Design self-healing pipeline architectures with comprehensive error handling, retry logic, and monitoring systems.
  • Drive performance optimization initiatives achieving significant improvements in throughput and latency.
  • Lead the design and implementation of enterprise-grade graph database schemas.
  • Architect sophisticated data models that balance query performance, analytical flexibility, and storage efficiency.
  • Design schema evolution strategies and implement zero-downtime migration frameworks.
  • Develop comprehensive ontologies and taxonomies.
  • Lead graph query optimization efforts and establish indexing strategies.
  • Partner closely with backend engineers, data scientists, cyber operations experts, and forward deployed analysts.
  • Work with SRE teams to ensure data infrastructure reliability and operational excellence.
  • Engage with government stakeholders to translate operational needs into technical data solutions.
  • Provide technical leadership in customer engagements and capability demonstrations.
  • Contribute to long-term technical strategy and roadmap planning for data platforms.
  • 8+ years of professional experience in data engineering, data architecture, or related roles with increasing technical leadership.
  • Expert-level proficiency with AWS data services including S3, Athena, Kinesis, Lake Formation, and Redshift.
  • Proven experience leading technical projects and mentoring junior data engineers.
  • Advanced programming skills in Python and/or Golang for building production-grade data pipelines and frameworks.
  • Extensive experience designing and implementing complex ETL pipelines using Apache Airflow or similar orchestration frameworks at scale.
  • Deep expertise in data modeling techniques for both relational and NoSQL databases.
  • Mastery-level experience with graph databases (Neo4j, AWS Neptune, or similar).
  • Expert knowledge of big data processing frameworks such as Apache Spark, Flink, or similar technologies.
  • Advanced SQL skills and proven experience with query optimization.
  • Extensive experience with data lake architectures and modern data warehouse solutions.
  • Deep understanding of data serialization formats and optimization techniques.
  • Expert knowledge of streaming data architectures and event-driven processing.
  • Advanced experience with containerization and infrastructure as code.
  • Understanding of distributed systems principles, consensus algorithms, and fault tolerance patterns.
  • Deep understanding of data security best practices.
  • Extensive experience implementing role-based access controls and data classification schemes.
  • Knowledge of data privacy principles and compliance requirements.
  • Understanding of zero-trust architecture principles.
  • Previous experience as a technical lead or senior data engineer in government, defense, or intelligence applications.
  • Track record of building data infrastructure for mission-critical systems.
  • Background in cybersecurity data analysis, threat intelligence platforms, or SIEM systems.
  • Expert knowledge of graph analytics and network analysis for cyber operations.
  • Deep understanding of cyber domain data including network flows, DNS logs, and threat feeds.
  • Expertise in geospatial data processing and visualization.
  • Experience with data mesh architectures and federated data systems.
  • AWS certifications or other relevant data engineering certifications.
  • Previous experience working with data scientists and ML engineers.
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