Data Engineer for DoD Cyber Ops | ETL, Spark, Cloud (TS/SCI)

Peraton; United States; On-site; USD 135,000 - 216,000; Full time

Job summary

Peraton seeks a Data Engineer to support Department of Defense Cyber Defense Command (DCDC) with defensive cyberspace operations and AI/ML security support. Fort Meade, MD-based role within the Analytic Development Team, focusing on data infrastructure, pipelines, and integration for analytic capabilities.

You will design ETL workflows, transform data for schema compliance, and ensure data quality across IoT streams, APIs, and legacy systems, while maintaining lineage and documentation.

Qualifications

• 8+ years with BS/BA; 6+ years with MS/MA; 3+ years with PhD
• Proficiency in Python, SQL, Scala
• Experience with Spark, Kafka, and Hadoop ecosystem
• Knowledge of data modeling and warehousing
• Understanding of streaming architectures
• Experience with cloud data services
• U.S. Citizenship required
• DoD TS with ability to obtain/maintain SCI clearance

Responsibilities

• Design and implement ETL workflows using Airflow, NiFi, or similar
• Develop data transformation logic for schema compliance
• Integrate data from IoT streams, APIs, and legacy systems
• Implement data validation and quality checks
• Optimize pipeline performance and reliability
• Maintain data lineage tracking and documentation

Skills

Python

SQL

Scala

Data modeling

Streaming architectures

Cloud data services

Education

BS/BA in CS or related

MS/MA in relevant field

PhD (optional)

Tools

Spark

Kafka

Hadoop ecosystem

React 18/19

HTML

CSS

JavaScript

TypeScript

GitLab

Flux CD

Kubernetes

Node.js

Express

MarkLogic

xQuery

Job description

Peraton seeks a Data Engineer to support Department of Defense Cyber Defense Command (DCDC) with defensive cyberspace operations and AI/ML security support. Fort Meade, MD-based role within the Analytic Development Team, focusing on data infrastructure, pipelines, and integration for analytic capabilities.

You will design ETL workflows, transform data for schema compliance, and ensure data quality across IoT streams, APIs, and legacy systems, while maintaining lineage and documentation.