Streaming Data Architect - Real-Time IoT Streaming Infrastructure | NATS/Kafka

Job Location: Remote, prefer the candidate is in proximity to Springfield, VA and greater DC area for access to Aberdeen Proving Ground, MD.

Travel Requirement: Up to 25%

Security Clearance: Active Secret clearance required (interim OK)

Citizenship: US Citizenship required

Sherpa 6 is seeking a highly experienced Streaming Data Architect to design and build real-time streaming infrastructure that moves sensor data from IoT devices in the field into the systems that turn it into decisions. This is a hands-on architecture role: you'll define how high volume, low-latency data moves through a distributed messaging backbone built on NATS, and you'll shape the patterns that keep it reliable even when devices are operating in constrained or disconnected conditions.

The ideal candidate has deep experience with modern streaming architectures and hands-on expertise with high-volume messaging tools such as Kafka, NATS, or similar distributed systems, and is excited to apply that expertise to mission-driven, sensor-heavy environments rather than a typical commercial data stack.

Key Responsibilities:

• Architect, design, and implement high performance streaming data platforms using NATS for IoT sensor data ingestion, processing, and distribution.
• Define and maintain message schemas, subject taxonomies, and overall data governance patterns for real-time event-driven systems.
• Develop scalable distributed streaming pipelines capable of handling high-throughput, low-latency, and bursty sensor data.
• Collaborate closely with engineering teams to define data models, communication protocols, and ingestion strategies across diverse IoT devices.
• Evaluate, select, and implement best-in-class frameworks, tooling, and architectural patterns for streaming analytics and durable messaging.
• Optimize streaming architecture for reliability, fault-tolerance, and operations in heterogeneous or constrained environments.
• Integrate streaming components seamlessly with cloud systems, microservices, and downstream analytics or storage platforms.