The
Data Software Engineer serves as the technical authority responsible for architecting, scaling, and governing the graph-centric data infrastructure that powers the company's simulation, analytics, and digital-engineering ecosystems. This role blends backend engineering, high-performance data processing, and advanced graph-based modeling to ensure that data relationships, APIs, and integration workflows are coherent, scalable, secure, and aligned with mission and product objectives. You will design and optimize knowledge-graph schemas, build high-throughput data services in Python/C++/Rust, define robust data-access and governance patterns, and collaborate closely with simulation, systems engineering, frontend, and DevOps teams to deliver reliable, mission-critical data capabilities across aerospace, defense, and other regulated environments.
Major Responsibilities- Architect and scale knowledge-graph infrastructure supporting simulation, analytics, and digital-engineering workflows.
- Design and optimize graph schemas for large, interconnected, and evolving data domains.
- Develop high-throughput backend services in Python, C++, or Rust for data-intensive workloads.
- Implement robust data-access layers including indexing, query optimization, and governance patterns.
- Build and maintain secure APIs across REST, GraphQL, and gRPC ecosystems.
- Ensure reliability and observability through logging, metrics, tracing, contract validation, and automated testing.
- Collaborate across engineering teams to define clean integration boundaries and support mission-critical workflows.
- Support CI/CD and DevOps integration for backend services and data pipelines.
- Enforce secure data practices including authentication, authorization, secrets management, and encryption.
Ideal Experience - STEM foundation - Bachelor's degree in Computer Science, Engineering, Mathematics, or STEM related field, or equivalent experience.
- Backend & data-service development - 1-5 years building backend systems, APIs, and data-driven services.
- API design expertise - REST, GraphQL, schema design, versioning, and integration best practices.
- High-performance backend programming - Python, C++, or Rust for distributed and performance-critical systems.
- Database schema & modeling - Relational (PostgreSQL), graph (Neo4j), and document databases.
- Data-access architecture - Indexing, query optimization, and governance for large-scale data domains.
- Service reliability fundamentals - Observability, error handling, contract validation, automated testing.
- API & data security - Authentication, authorization, secrets management, encryption.
- CI/CD integration - Experience integrating backend services into CI/CD pipelines.
- Cross-functional collaboration - Ability to work with simulation, systems engineering, frontend, and DevOps teams.
Desired Skills - Multi-protocol API development - REST, gRPC, SOAP, GraphQL.
- Graph-based data modeling - Metadata lineage, digital-thread architectures, agent-reasoning structures.
- High-throughput data APIs - Streaming systems, binary formats, performance tuning.
- HPC-adjacent workflows - Simulation data, scientific computation, data-dense analytics.
- Microservice architectures - Containerized deployments and service-to-service communication.
- API design for diverse consumers - Interfaces for UIs, pipelines, and automated systems.
- Regulated industry exposure - Aerospace, defense, or other high-integrity domains.
- Open-source contributions - Backend frameworks, API libraries, database tooling, schema governance systems.
- Security eligibility - U.S. Citizen; able to obtain and maintain DoD Secret clearance (TS/SCI preferred).
