Palantir Foundry Engineer — Data Pipelines & Ontologies

Xinova Group; Philadelphia (Philadelphia County); Hybrid; USD 110,000 - 160,000; Full time

Job summary

Xinova Group is seeking an experienced Palantir Foundry Engineer to implement and enhance its data platform. You will integrate legacy systems, develop operational data solutions, and transform source data into production-ready models and workflows.

The role emphasizes hands-on Python/SQL, data pipeline development, and ontology work within Foundry, with initial on-site activity in Camden, NJ and later remote flexibility as needed.

Qualifications

• Ideally 5-10 years of overall industry experience in data engineering, software engineering, data modelling, or a related technical discipline.
• Mandatory hands-on experience with Python and SQL.
• Strong understanding of data engineering principles, data modelling, and data integration.
• Proven experience developing and maintaining production data pipelines and data processing systems.
• Experience with ETL/ELT processes, data transformations, and integrating multiple source systems.
• Ability to work with complex data structures and translate business requirements into effective data models.
• Experience building functional data-driven tools or operational systems beyond static dashboards and reporting.
• Strong problem-solving skills and the ability to troubleshoot complex technical challenges independently.
• Excellent communication skills, with the ability to engage directly with technical and non-technical stakeholders.
• Must be based in the United States and able to accommodate the initial on-site requirements in Camden, New Jersey.

Responsibilities

• Develop, enhance, and maintain data solutions within Palantir Foundry, including building and extending the ontology layer.
• Design and implement scalable data pipelines to ingest, transform, and process information from multiple legacy and proprietary systems.
• Map complex source data into consistent data models and Foundry ontologies to support downstream business processes.
• Build and maintain reliable ETL/ELT workflows to ensure data is accurately processed, structured, and accessible.
• Integrate disparate systems with different data formats, structures, and standards into a unified data environment.
• Develop functional, data-driven tools and operational systems that enable users to interact with data and support business decisions.
• Work with structured datasets, data transformations, and business-oriented data models to solve complex engineering challenges.
• Collaborate with technical teams, business stakeholders, and customer representatives to gather requirements and understand existing workflows.
• Translate evolving business requirements and customer feedback into practical technical solutions.
• Support the development of data solutions that improve healthcare claims processing, reimbursement workflows, and operational efficiency.
• Troubleshoot data quality issues, integration challenges, and pipeline performance problems across complex data environments.
• Maintain, enhance, and scale production systems as business requirements and customer needs evolve.
• Take ownership of technical challenges, identify opportunities for improvement, and deliver solutions with minimal supervision.
• Work on-site with the customer initially to develop an understanding of their systems, workflows, and business requirements before transitioning towards a more remote working arrangement.

Skills

Python

SQL

Data Modeling

Data Integration

ETL/ELT

Tools

Palantir Foundry

PySpark

Databricks

Snowflake

TypeScript

Job description

Xinova Group is seeking an experienced Palantir Foundry Engineer to implement and enhance its data platform. You will integrate legacy systems, develop operational data solutions, and transform source data into production-ready models and workflows.

The role emphasizes hands-on Python/SQL, data pipeline development, and ontology work within Foundry, with initial on-site activity in Camden, NJ and later remote flexibility as needed.