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# Data Engineer - Spark | Kafka | NIFI |

- **Company:** Kforce Inc.
- **Location:** Winchester, VA, United States
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Big Data, Data Architecture, Data Infrastructure, Data Integrity, Data Security, Data Systems, Distributed Data Store, Systems Integration, Enterprise Data Management, Apache Spark, Containerization, Data Lakes, Apache Kafka, Apache Nifi, Data Management, Data Pipelines, Devsecops
- **Published:** July 14, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9029007/data-engineer-spark-kafka-nifi

## About the Role

Active Top Secret clearance
Strong experience architecting and implementing enterprise data platforms
Experience with distributed data technologies including Spark, Kafka, and NiFi
Experience designing and supporting data lakes or lakehouse architectures
Experience working with AWS-based data solutions
Experience integrating or supporting DevSecOps practices
Experience working with large, complex datasets in secure or regulated environments
Ability to operate at a senior/SME level, owning solutions end-to-end

## Description

We are seeking a SME-Level Data Engineer to support a mission-critical federal program focused on advanced data platforms, operational intelligence, and national security initiatives.
This is a high-impact, hands-on role centered on architecting and implementing enterprise-scale data solutions in secure environments. Your work will directly support decision advantage and operational readiness.
You will lead the development of distributed data platforms and modern data architectures, leveraging cloud-native technologies while operating in a highly collaborative, mission-driven environment., Lead the architecture and implementation of enterprise data platforms using AWS services
Design and develop distributed data solutions using Spark, Kafka, and NiFi
Build and optimize data lakes and lakehouse architectures
Drive performance tuning and optimization of data processing workflows
Support integration of DevSecOps practices into data platform development
Collaborate with cross-functional teams across engineering, analytics, and infrastructure
Ensure data integrity, scalability, and reliability across large datasets
Support secure data handling and compliance requirements within a cleared environment


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