Cloud Engineer - AWS Data Pipelines
Competitive
You'll complete your application on the employer's website.
Competitive
You'll complete your application on the employer's website.
Job type
Salary
Competitive
Location
Sector
Posted
20 days ago
DNI (Delaware Nation Industries) is seeking a Data Engineer to support the Joint Warfare Analysis Center under the Air Force JWAC IT Services Task Order 2. The role designs, secures, monitors, and optimizes AWS cloud-native data solutions supporting analytics, AI/ML, agentic services, and LLMs, while integrating FinOps and Zero Trust security practices.
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
Company
Tribally owned federal contractor providing IT, cybersecurity, and professional services
Oklahoma City, Oklahoma, USA
https://dnigov.com/
Founded in 2015
501-1000 employees
Qualifications
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
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
Cloud-native data architecture and engineering
AWS services and serverless technologies
ETL/ELT development and data integration
Python and SQL
AI/ML data preparation and infrastructure
FinOps and cloud cost optimization
Zero Trust data security
Technical documentation and briefing development
Requirements analysis and stakeholder communication
Independent problem-solving and collaboration
At least three years of full-time experience in computer science, data engineering, or data science, including hands-on software development lifecycle experience.
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.
At least one year of experience implementing cloud-native data security controls, including IAM, encryption, and network segmentation.
Required skills
AWS, Data Engineering, Amazon Redshift, Amazon Athena, AWS Glue Data Catalog, AWS Lake Formation, Python, SQL, Jupyter, Amazon SageMaker Studio, Feature Engineering, Cloud Data Security
Experience
3+ years
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