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# DevOps Engineer- TS/SCI Clearance

- **Company:** V2X Inc
- **Location:** McLean, VA, United States
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Bash Shell, Information Engineering, Data Stores, DevOps, Elasticsearch, MapReduce, Apache Hive, Python (Programming Language), Node.Js, NoSQL, Operational Databases, Ansible, AWS Cdk, Apache Spark, Git, Cloudformation, Amazon Relational Database Service, Information Technology, Apache Nifi, Presto, Hardware Infrastructure, Restful APIs, Terraform, Docker, Jenkins, Programming Languages
- **Published:** September 5, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9145303/devops-engineer-tssci-clearance

## About the Role

* Bachelors degree in Computer Science, IT, Mathematics or equivalent experience, * Extensive familiarity with AWS services to include CloudFormation, EC2, S3, and RDS
 * CloudFormation, Ansible, Git, Jenkins, Bash
 * Programming Languages: Python, Java or Scala
 * Processing Tools: Elasticsearch, Spark, Nifi, and/or Docker
 * Datastore Types: Graph, NoSQL, and/or Relational
 * Familiarity in ISSE roles and responsibilities
 * Active TS/SCI with Poly required

Preferred Qualifications:

 * Familiarity with AWS CDK
 * Terraform, Packer
 * Design Concepts: REST APIs
 * Programming Languages: JavaScript/NodeJS
 * Processing Tools: Presto/Trino, MapReduce, Hive

## Description

V2X is seeking a DevOps Engineer with an active TS/SCI with Poly clearance who will be responsible for taking a leadership role in refactoring existing data workflows from an on-premises infrastructure to the cloud. The ideal candidate is a hands-on developer with extensive DevOps experience who can identify and implement the appropriate cloud alternative to on-prem resources., Our DevOps Engineers are responsible for the full data lifecycle - from exploratory data analysis to the upkeep of production data flows. The DevOps Data Engineer focuses a majority of their time supporting the underlying environment and infrastructure used by the rest of the Data Engineering and Data Science teams.


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