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# Palantir Data Engineer

- **Company:** Kforce Inc.
- **Location:** Tysons, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Big Data, Cloud Engineering, Information Systems, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Data Structures, Data Systems, Distributed Computing Environment, Python (Programming Language), Software Architecture, SQL Databases, Enterprise Data Management, Pyspark, Information Technology, Data Management, Software Version Control, Data Pipelines, Devsecops
- **Published:** September 25, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9195165/palantir-data-engineer

## About the Role

* Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical discipline, or equivalent professional experience
 * 8+ years of experience designing and developing production-grade data engineering solutions
 * Strong proficiency with Python, SQL, and modern data engineering methodologies
 * Experience designing and implementing data pipelines and enterprise data products on large-scale analytics or data platforms
 * Experience with data modeling, ontology design, data governance, data quality, and lineage management
 * Strong software engineering fundamentals, including testing, version control, CI/CD, and monitoring practices
 * Experience supporting complex enterprise or government environments
 * Ability to make architectural decisions and drive technical solutions from concept through deployment, * Experience working within large-scale operational, logistics, acquisition, financial, or program management environments
 * Experience with modern enterprise data platforms, analytics ecosystems, or digital transformation initiatives
 * Experience with distributed data processing technologies such as PySpark or similar frameworks
 * Knowledge of cloud-native architectures, DevSecOps practices, and infrastructure-as-code concepts
 * Experience developing mission-critical data products that support operational decision-making and business intelligence initiatives
 * Strong stakeholder engagement and communication skills with both technical and non-technical audiences

## Description

We are seeking an experienced Data Engineer to support a high-visibility federal modernization initiative focused on building authoritative enterprise data products that drive mission operations, analytics, and decision-making. This role will be responsible for architecting and developing scalable data solutions, including data pipelines, models, and enterprise data frameworks within modern data platforms.

This is a senior-level individual contributor position for an engineer who can make sound architectural decisions, develop production-grade data solutions, and help elevate engineering standards across the organization.

The program offers the opportunity to work on complex data challenges supporting large-scale operational environments, leveraging modern technologies and advanced analytics platforms while collaborating with stakeholders across technical and business domains., * Own the architecture, design, and implementation of scalable data pipelines and enterprise data products

 * Integrate, transform, and manage data from multiple enterprise and operational data sources
 * Develop and maintain data models, ontologies, and data structures that support applications, reporting, analytics, and decision-making
 * Design solutions that emphasize data quality, governance, lineage, observability, security, and long-term maintainability
 * Establish engineering standards for testing, source control, deployment, monitoring, and operational support
 * Build and optimize large-scale data processing workflows and data integration solutions
 * Partner closely with software engineers, product teams, analysts, and business stakeholders to deliver impactful data products
 * Participate in architectural reviews and provide technical leadership on complex data initiatives
 * Mentor team members and contribute to engineering best practices across the organization
 * Troubleshoot and resolve complex data integration, quality, and performance challenges


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