Palantir Lead​/Architect

Data Engineer

Pay Range: $75hr - $80hr

Responsible for designing and implementing enterprise-scale data solutions using the Palantir Foundry platform.

The role involves developing data pipelines, ontology models, AI-driven workflows, and advanced analytics solutions while collaborating with business stakeholders to deliver scalable and secure data applications.

Responsibilities:

• Design and implement end-to-end data solutions using the Palantir Foundry platform.
• Build and manage data pipelines for ingestion, transformation, and orchestration.
• Develop and maintain Foundry Ontology models to represent business entities and relationships.
• Work on Contour and AIP for AI and machine learning driven workflows and decision support.
• Utilize Quiver for advanced analytics and data exploration use cases.
• Collaborate with business stakeholders to translate requirements into data-driven applications and workflows.
• Ensure data governance, lineage, security, and performance optimization.
• Drive best practices for data engineering, architecture, and deployment within the Palantir ecosystem.
• Support production deployments, troubleshooting, and optimization of pipelines and applications.
• Lead solution discussions and provide technical guidance to project teams.

Requirement/Must Have:

• 10+ years of overall IT experience with strong focus on data and platform engineering.
• Hands-on experience with Palantir Foundry.
• Experience with Pipeline Builder and Code Repositories within Foundry.
• Experience with Ontology modeling.
• Experience with Contour and AIP.
• Experience with Quiver.
• Strong expertise in data engineering and pipeline development.
• Strong expertise in data modeling and schema design.
• Knowledge of distributed data processing concepts.
• Proficiency in Python and SQL.
• Experience with data governance and data quality frameworks.
• Ability to work in client-facing environments and drive technical discussions.

Should Have:

• Experience with AWS cloud platform.
• Exposure to AI and machine learning integration and use-case development.
• Knowledge of data mesh and data product architecture.
• Strong understanding of enterprise data ecosystems.
• Experience working in onsite-offshore collaboration models.

Skills:

• Palantir Foundry.
• Pipeline Builder.
• Ontology modeling.
• Contour and AIP.
• Quiver.
• Data engineering.
• Data pipeline development.
• Data modeling and schema design.
• Distributed data processing.
• Python.
• SQL.
• Data governance and data quality.
• Cloud platforms including AWS.
• AI and machine learning integration.
• Stakeholder communication and leadership.

Qualification And

Education:

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or related field preferred.
• Advanced certifications or cloud certifications preferred.