Foundry Data Engineer

About the Role

We’re seeking an experienced Data Engineer with strong expertise in Palantir Foundry to support the design, development, and optimization of enterprise-scale data workflows. This role will work closely with business stakeholders, analysts, and engineering teams to build robust data pipelines and deliver actionable insights.

Key Responsibilities

• Build and maintain Foundry data pipelines to integrate siloed enterprise data (ERP, CRM, operational systems) into a unified platform for decision-making
• Develop transformation logic to standardize and clean inconsistent data across business units, enabling accurate reporting and analytics
• Design and manage ontology layers to reflect real-world business entities (e.g., customers, assets, transactions) for operational use cases
• Partner with stakeholders to translate complex business processes into scalable data workflows that support daily operations
• Monitor pipeline performance and resolve data quality issues to ensure reliability formission-critical dashboards and applications
• Support deployment of data products that drive use cases such as forecasting, supply chain optimization, or risk analysis

Required Qualifications

• 3–6+ years of experience in data engineering or analytics engineering
• 3+ Hands-on experience with Palantir Foundry (pipelines, transforms, ontology, Code Repos)
• Strong SQL and Python skills
• Experience with distributed data processing and ETL/ELT frameworks
• Familiarity with Git-based workflows and CI/CD practices
• Ability to work in a fast-paced, client-facing environment

Preferred Qualifications

• Experience in finance, healthcare, or supply chain domains
• Exposure to cloud platforms (AWS, Azure, or GCP)
• Experience supporting operational analytics or real-time decision systems
• Prior consulting or stakeholder-facing experience

Work Environment

• Hybrid model: 2–3 days onsite in NYC, remainder remote
• Collaborative, cross-functional team environment
• Opportunity to work on high-impact data initiatives