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Full-time

Cloud Engineer - AWS Data Pipelines

Competitive

Dahlgren, VAIT & TechnologyPosted 20d ago

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Role overview

Job type

Full-time

Salary

Competitive

Location

Dahlgren, VA

Posted

20 days ago

Job description

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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