Peraton is seeking a highly experienced Senior Systems Engineer to lead the design, development, and implementation of our enterprise-scale data models and ontologies. This role is critical in transforming disparate data sources into a cohesive, searchable, and semantically rich knowledge graph. You will serve as a technical authority, guiding the evolution of our "Entity-Evidence" frameworks and ensuring the reliability of our distributed data services.

Key Responsibilities:

• Ontology & Model Engineering:
• Lead the design and implementation of complex domain ontologies and logical data models to support advanced analytics and discovery.
• Develop and refine schemas for graph databases (Neo4j), ensuring optimal relationship modeling and query performance.
• Establish standards for entity resolution, taxonomy management, and metadata tagging across the enterprise.
• Oversee the ingestion of "EntitySourceDocuments" and associate evidence into unified semantic structures.

Systems Architecture & Integration:

• Design and manage high-throughput data pipelines using distributed streaming platforms like Apache Kafka.
  • • Implement sophisticated message-key strategies and topic compaction to ensure data integrity and system efficiency.
    • Orchestrate containerized services within Kubernetes (K8s), leveraging Custom Resource Definitions (CRDs) and Operators for complex stateful workloads.
    • Integrate diverse data assets-from relational stores to unstructured documents-into a synchronized, scalable backend architecture.

Technical Leadership & Governance:

• Provide expert-level support for model implementation, ensuring alignment between conceptual models and physical deployments.
  • • Mentor junior engineers on best practices in Java/Spring Boot development, API documentation (OpenAPI/Swagger), and cloud-native patterns.
    • Collaborate with data scientists and stakeholders to translate business requirements into technical specifications and architectural diagrams.

Reliability & Performance:

• Conduct deep-dive troubleshooting for complex system bottlenecks, particularly within Kafka clusters and graph database clusters.
  • • Define and implement monitoring and observability standards using Prometheus, Grafana, and ELK.
    • Ensure the long-term scalability and maintainability of the "arbitranch" and "KEA" service ecosystems.

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