Data Engineer 102267 with Security Clearance

Information Technology Engineering CorporationArlington, VA🇺🇸United StatesPosted Oct 16, 2026

Why This Role Stands Out

This hybrid Data Engineer role offers a fantastic opportunity to build and maintain critical data infrastructure for the DoD and Intelligence Community, fostering significant career growth and skill development within a reputable organization. You'll thrive here if you're a proactive problem-solver eager to collaborate and contribute to innovative data solutions, with the added benefit of a competitive compensation package and comprehensive benefits. Apply now to leverage your expertise and make a real impact!

Quick Overview

Seniority

Mid Senior

Employment type

Employee

Work mode

Hybrid

Location

Arlington, VA, United States

Posted

6 days ago

Data PipelineMachine Learning

Job Description

Data Engineer
Location: Alexandria, VA/Springfield, VA/Arlington, VA/Herndon, VA/Chantilly, VA
Required Clearance: Secret/Top Secret/Top Secret/SCI ManpowerGroup Public Sector (MGPS) provides Skilled Experts and Leading-Edge Solutions to Support Our Nation’s Most Critical Intelligence, Defense and Civilian Missions. MGPS specializes in solving our clients’ diverse linguistic, technical and data management challenges created by the dramatic rise in the volume, variety and complexity of open source data. We harness machine learning, artificial intelligence and the latest data acquisition and mining tools, paired with expert human skills to provide customized solutions for every customer. U.S.

Citizenship Mandatory: Due to our US federal government contract, candidates for this position are required to be a US Citizen and will be subject to a background investigation.

Job Responsibilities

Design, build, and maintain the core data infrastructure and pipelines necessary to ingest, process, store, and transform data for various consumers.
Develop and operate automated, end-to-end data pipelines, create and maintain data models and schemas, and contribute to the overall scalability, reliability, and security of the data platform.
Implement data processing frameworks and technologies, design and optimize data storage solutions, and develop data transformation logic to support analytics requirements.
Implement data quality checks and validation procedures, establish data lineage tracking mechanisms, and troubleshoot data pipeline issues.
Collaborate with data scientists and analysts to understand data requirements, work with security teams to implement data protection measures, and stay current with data engineering technologies and best practices.
Document data architecture and pipelines, participate in data governance activities, and contribute to continuous improvement of data engineering processes.