Senior Data Engineer - TS/SCI
$131,300–$237,350 year
HybridBethesda, Maryland, United States
Job Summary
Design, develop, and optimize scalable data management solutions supporting advanced analytics and AI/ML workloads by building Elasticsearch and graph-based data platforms for hierarchical data discovery. Manage large-scale ingestion pipelines, automate data transformation and validation, and optimize graph and search infrastructure for high availability under heavy analytical loads. Collaborate with data scientists, software engineers, and infrastructure teams to deploy stateful services in Kubernetes and integrate microservices into broader applications. Participate in SAFe Agile development, including sprint planning, design reviews, and technical demonstrations, while ensuring compliance with security policies and delivering high-quality software.
Required Qualifications
- Bachelor's degree in Computer Science, Data Engineering, or related field
- 12–15 years of relevant experience
- Master's degree
- 10–13 years of experience
- Active Top Secret/SCI clearance
- Ability to obtain and maintain a Polygraph
- Elasticsearch/OpenSearch architecture
- Index design
- Mappings
- Analyzers
- Query optimization
- Graph databases
- JanusGraph
- Neo4j
- TigerGraph
- Amazon Neptune
- Memgraph
- Data modeling
- Hierarchical datasets
- Highly connected datasets
- Large-scale ETL/ELT pipeline development
- Kubernetes deployment
- Kubernetes operations
- Stateful data services
- Distributed storage systems
- High-volume data ingestion
- Python
- Java
Desired Qualifications
- Experience supporting AI/ML and data science workflows
- Apache Kafka
- Streaming technologies
- Linux
- Containerization
- CI/CD pipelines
- Infrastructure-as-Code
- Graph analytics frameworks
- Graph traversal
- Centrality
- Community detection
- Similarity analysis
- Link prediction
- Keycloak
- Security best practices
- AuthN/Z
- Secrets management
- Building and maintaining microservices in Kubernetes
- CloudFormation
- Terraform
- Pulumi
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