Palantir Foundry Lead-Architect
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Job Location:
New York City, NY - USA
Monthly Salary:
Not Disclosed
Posted on:
11 hours ago
Vacancies:
1 Vacancy
Job Summary
We are seeking a highly experienced Foundry Lead Data Engineer to architect develop and optimize scalable data solutions using Palantir Foundry. This senior role is ideal for a data engineering expert who thrives in complex ontology-aware environments and can lead the design of robust data pipelines and applications that drive actionable insights.
You will play a pivotal role in shaping our data strategy collaborating with stakeholders across the organization and ensuring the integrity performance and cost-efficiency of our data ecosystem. While familiarity with Generative AI (GenAI) is a plus your core expertise should lie in data architecture pipeline development and Foundry platform mastery.
Key Responsibilities
Data Architecture & Pipeline Engineering
Design build and maintain end-to-end ETL/ELT pipelines using PySpark Spark SQL and Python.
Architect scalable data frameworks that support high-performance analytics and operational workflows.
Conduct data cleansing transformation and validation to ensure data quality and consistency.
Palantir Foundry Platform Expertise
Configure and manage data connections Pipeline Builder and Contour for data exploration and visualization.
Develop and maintain ontology objects ensuring semantic consistency and reusability across applications.
Manage code repositories and version control within Foundry promoting modular and maintainable engineering practices.
Ontology-Aware Application Development
Collaborate with data owners and domain experts to ingest transform and model data into ontology-driven applications such as Workshop and Quiver.
Maintain clarity on the end-to-end architecture and data flow ensuring seamless integration from ingestion to ontology.
Cross-Functional Collaboration & Leadership
Partner with data scientists analysts and business stakeholders to translate requirements into scalable data solutions.
Engage with senior leadership to maintain a feedback loop for Foundry program improvements.
Provide mentorship and technical guidance to junior engineers and analysts.
Operational Excellence & Cost Management
Establish and maintain cost monitoring and reporting for Foundry-related operations.
Lead efforts in troubleshooting performance tuning and platform stability.
Continuous Improvement & Innovation
Stay current with Foundry platform updates emerging features and best practices.
Identify opportunities for automation optimization and innovation in data workflows.
Explore and evaluate GenAI capabilities for potential integration into data processes.
Required Qualifications
8 years of experience in data engineering or related roles.
Strong proficiency in PySpark Spark SQL and Python.
Deep hands-on experience with Palantir Foundry including:
Data Connections
Pipeline Builder
Contour
Code Repositories
Ontology Management
Workshop and Quiver
Solid understanding of data modeling data governance and access control.
Proven ability to troubleshoot complex data issues and optimize performance.
Excellent communication and collaboration skills.
Preferred Qualifications
Experience with cloud platforms (e.g. Azure).
Familiarity with Snowflake and its integration with Foundry.
Exposure to Generative AI (GenAI) and its application in data workflows.
Knowledge of data security compliance and metadata management.
You will play a pivotal role in shaping our data strategy collaborating with stakeholders across the organization and ensuring the integrity performance and cost-efficiency of our data ecosystem. While familiarity with Generative AI (GenAI) is a plus your core expertise should lie in data architecture pipeline development and Foundry platform mastery.
Key Responsibilities
Data Architecture & Pipeline Engineering
Design build and maintain end-to-end ETL/ELT pipelines using PySpark Spark SQL and Python.
Architect scalable data frameworks that support high-performance analytics and operational workflows.
Conduct data cleansing transformation and validation to ensure data quality and consistency.
Palantir Foundry Platform Expertise
Configure and manage data connections Pipeline Builder and Contour for data exploration and visualization.
Develop and maintain ontology objects ensuring semantic consistency and reusability across applications.
Manage code repositories and version control within Foundry promoting modular and maintainable engineering practices.
Ontology-Aware Application Development
Collaborate with data owners and domain experts to ingest transform and model data into ontology-driven applications such as Workshop and Quiver.
Maintain clarity on the end-to-end architecture and data flow ensuring seamless integration from ingestion to ontology.
Cross-Functional Collaboration & Leadership
Partner with data scientists analysts and business stakeholders to translate requirements into scalable data solutions.
Engage with senior leadership to maintain a feedback loop for Foundry program improvements.
Provide mentorship and technical guidance to junior engineers and analysts.
Operational Excellence & Cost Management
Establish and maintain cost monitoring and reporting for Foundry-related operations.
Lead efforts in troubleshooting performance tuning and platform stability.
Continuous Improvement & Innovation
Stay current with Foundry platform updates emerging features and best practices.
Identify opportunities for automation optimization and innovation in data workflows.
Explore and evaluate GenAI capabilities for potential integration into data processes.
Required Qualifications
8 years of experience in data engineering or related roles.
Strong proficiency in PySpark Spark SQL and Python.
Deep hands-on experience with Palantir Foundry including:
Data Connections
Pipeline Builder
Contour
Code Repositories
Ontology Management
Workshop and Quiver
Solid understanding of data modeling data governance and access control.
Proven ability to troubleshoot complex data issues and optimize performance.
Excellent communication and collaboration skills.
Preferred Qualifications
Experience with cloud platforms (e.g. Azure).
Familiarity with Snowflake and its integration with Foundry.
Exposure to Generative AI (GenAI) and its application in data workflows.
Knowledge of data security compliance and metadata management.
