Note: The job is a remote job and is open to candidates in USA. Redhawk Administrative Services (RAS) is seeking a Mid-Level Data Platform Engineer to support the development and operation of a modern data environment for Navy financial management initiatives. The role involves building and maintaining data pipelines and transformation processes within Palantir Foundry and the Jupiter data platform.

Responsibilities

• Develop and maintain Python-based data pipelines and transformation workflows within Palantir Foundry and the Jupiter platform
• Build ingestion pipelines integrating financial management, logistics, property, and other enterprise datasets
• Implement transformation logic to prepare raw datasets for curated data layers and ontology population
• Support dataset lifecycle management including refresh schedules, validation checks, and pipeline monitoring
• Troubleshoot pipeline failures and assist in maintaining platform data reliability and stability
• Maintain dataset lineage awareness and support platform data integrity practices
• Assist with integrating enterprise system data into the platform environment
• Collaborate with ontology engineers to ensure pipelines populate ontology objects and platform data structures correctly
• Document pipelines and transformation logic to support maintainability of the platform

Skills

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or related field, or equivalent experience
• 4–7 years experience in data engineering or platform engineering roles
• Experience developing Python-based data pipelines
• Experience building ETL/ELT pipelines and data transformation workflows
• Experience working with enterprise data platforms such as Palantir Foundry, Databricks, AWS data platforms, or similar distributed data environments
• Strong Python development skills for data processing and pipeline development
• Experience with SQL and data transformation frameworks
• Familiarity with distributed data platforms and large-scale data environments
• Strong troubleshooting and problem-solving skills in data pipeline operations
• Ability to collaborate with platform engineers, ontology engineers, and functional stakeholders
• Experience integrating datasets from enterprise systems (ERP, financial systems, logistics systems, etc.)

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