Platform Engineer

Volume Integration•Herndon, VA

9d•Onsite

About The Position

Looking for an opportunity to work at the intersection of data engineering and modern platform technologies? Join NS2 Mission as a Palantir Platform Engineer in Herndon, VA, supporting the development of scalable data solutions within the Palantir Foundry ecosystem. In this role, you'll bridge data engineering and platform capabilities by integrating custom ETL workflows with Palantir tooling, improving visibility into data processing, and enabling reliable movement and transformation of large datasets. You'll apply your expertise in Palantir Foundry, data ontology, PySpark, Python, monitoring, and DevOps to build efficient data pipelines and prepare trusted data products for advanced analytics and exploitation.

Requirements

Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or a related technical discipline (or equivalent combination of education and experience).
Professional experience developing and supporting data engineering or platform engineering solutions.
Hands-on experience with Palantir Foundry or comparable enterprise data platforms.
Strong understanding of data ontology and data modeling concepts.
Demonstrated ability to build, integrate, and maintain ETL pipelines.
Strong proficiency in Python and PySpark for data processing and pipeline development.
Experience implementing logging, monitoring, and observability solutions for data or software platforms.
Understanding of data governance, data quality, and validation practices.
Familiarity with DevOps methodologies, automated deployment, and operational support.
Strong analytical and troubleshooting skills with the ability to work across complex data environments.

Nice To Haves

Experience integrating custom ETL conditioners or workflows directly with Palantir Foundry tooling.
Background improving data pipeline observability and accelerating data conditioning workflows.
Experience providing end-to-end visibility into data transformation and processing activities.
Experience leveraging AI/ML or automation to enhance data pipeline performance or efficiency.
Familiarity with integrating validated data products into analytics, visualization, or data exploitation platforms.
Experience working with large-scale or distributed data processing environments.
Familiarity with cloud-based data platforms and modern infrastructure technologies.
Experience supporting Intelligence Community or Department of Defense programs.

Responsibilities

Design, develop, and integrate scalable ETL pipelines within the Palantir Foundry ecosystem.
Connect custom ETL conditioners and data workflows with Palantir tooling to improve pipeline visibility, monitoring, and operational efficiency.
Develop data processing solutions using Python and PySpark to support large-scale ingestion, transformation, and conditioning.
Apply Ontology and Data Ontology concepts to structure, organize, and contextualize data for downstream use.
Implement logging, monitoring, and observability capabilities that provide insight across data transformation workflows.
Establish and maintain data validation and quality controls to ensure reliable, trusted data products.
Apply data governance practices throughout the data lifecycle, from ingestion and transformation through delivery and analytics integration.
Leverage AI and automation techniques to improve data pipeline performance, efficiency, and scalability.
Support deployment, configuration, and operational sustainment of data platform capabilities using modern DevOps practices.
Collaborate with data engineers, platform teams, analysts, and mission stakeholders to translate requirements into effective data solutions.
Prepare validated data products for integration with analytics and exploitation tools.