DNI is seeking a highly qualified Data Engineer to support the Joint Warfare Analysis Center (JWAC) under Air Force JWAC IT Services (JITS) Task Order 2. The Data Engineer will design, implement, secure, monitor, and optimize cloud-native data engineering solutions that support data science, artificial intelligence/machine learning (AI/ML), agentic services, hosted models, and large language model (LLM) optimization. The role integrates data engineering, FinOps, Zero Trust security, and AI/ML infrastructure responsibilities within a single position.
This position is expected to work onsite at JWAC in Dahlgren, Virginia, supporting a TS/SCI/SAP environment.
Responsibilities- Design, build, troubleshoot, and tune end-to-end cloud-native data engineering solutions using AWS platform and software services.
- Develop and administer data ingestion, ETL, integration, transformation, validation, publication, and lifecycle-management workflows.
- Integrate structured and unstructured data from databases, web services, message traffic, data dumps, documents, and other sources.
- Design data architectures and managed data stores that support analytics, feature engineering, model training, and real-time inference.
- Develop solutions using AWS services such as AWS Glue, Amazon Athena, Amazon Redshift, Amazon Kinesis, AWS Lake Formation, AWS Glue Data Catalog, Amazon RDS, Amazon Aurora, and Amazon DynamoDB.
- Create REST APIs and web services to expose data to JWAC-developed applications and analytical systems.
- Support AI/ML infrastructure, including model hosting, model-ready datasets, agentic workflow orchestration, retrieval-augmented generation (RAG), and LLM integration and optimization.
- Develop automation, monitoring, alerting, and self-healing capabilities using AWS-native tools such as Amazon CloudWatch and AWS CloudTrail.
- Implement data discovery and search capabilities using services such as Amazon OpenSearch Service, AWS Glue Data Catalog, and Amazon Kendra.
- Apply FinOps practices, including resource tagging, cost allocation, right-sizing, storage tiering, query optimization, budget monitoring, cost-per-workload analysis, and AI/LLM cost tracking.
- Implement DoD Zero Trust and NIST SP 800-53 Rev. 5 security controls across data engineering and AI service environments.
- Configure identity and access management, least-privilege access, encryption at rest and in transit, network segmentation, certificate management, and security monitoring.
- Support security assessments, compliance documentation, data-flow diagrams, control mappings, and authorization activities.
- Gather requirements, evaluate data sources, communicate technical recommendations, and document architecture, processes, costs, risks, and implementation decisions.
- Develop briefings, technical proposals, operating procedures, user documentation, training materials, and knowledge-transfer products.
- Collaborate with Government stakeholders, data scientists, analysts, cybersecurity personnel, cloud engineers, and other technical teams.
Requirements- Bachelor of Science degree in computer science, computer engineering, data engineering, data science, or a related technical discipline.
- At least three years of full-time experience in computer science, data engineering, or data science, including hands-on software development lifecycle experience.
- Recent experience designing or implementing data engineering solutions or cloud-native systems on AWS.
- At least one year of experience with cloud-native data warehouse or analytics platforms, such as Amazon Redshift, Amazon Athena, AWS Glue Data Catalog, or AWS Lake Formation.
- At least one year of experience supporting data science applications and analytical tools such as Python, Jupyter, Amazon SageMaker Studio, AWS Glue DataBrew, or Amazon QuickSight.
- Experience preparing data for data scientists, including data preparation, feature engineering, and model-ready dataset construction.
- At least one year of experience implementing cloud-native data security controls, including IAM, encryption, and network segmentation.
- Ability to meet DoD 8140.03 requirements for the applicable work roles, including Primary Work Role 422 - Data Architect (Intermediate).
- Ability to obtain and maintain the required TS/SCI/SAP access.
- Ability to work onsite in Dahlgren, Virginia, during established core hours and support scheduled maintenance activities as required.
Preferred Qualifications- Experience with Amazon Bedrock, Knowledge Bases, RAG architectures, agentic services, or LLM prompt and token optimization.
- Experience with AWS Security Hub, Amazon GuardDuty, AWS KMS, AWS IAM Identity Center, and AWS Certificate Manager.
- Experience applying NIST SP 800-53 Rev. 5 and DoD Zero Trust Architecture principles.
- Experience with FinOps dashboards and tools such as AWS Cost Explorer, AWS Budgets, and AWS Cost and Usage Reports.
- Experience with data discovery, federated search, geospatial or non-geospatial search, and knowledge-management solutions.
- Experience supporting classified or highly regulated Department of Defense environments.
- AWS certifications, data engineering certifications, or relevant DoD cybersecurity certifications.
