Palantir Foundry Use Case Engineer

• Configure, build, and operationalize business use cases on the Palantir Foundry platform.

• Focus on:

• Use-case configuration
• Ontology modeling
• Data pipeline development
• Business-facing analytics
• Work within an agile, business-led 2-week sprint model.
• Participate as part of a Palantir Center of Excellence (CoE) delivery model.
• Translate business problems into Palantir-native solutions.
• Focus on rapid configuration and delivery rather than heavy custom coding.

Mandatory Skills

• Hands-on experience configuring Palantir Foundry use cases, including, Use Case Configuration & Delivery

• Configure end-to-end Palantir Foundry use cases covering:

• Data ingestion
• Ontology setup
• Data transformations
• Analytics dashboards

• Build business-facing applications using:

• Datasets
• Pipelines
• Ontology Manager
• Contour
• Workshop
• Slate
• Work in 2-week Agile sprints.
• Participate in frequent business demonstrations and feedback sessions.
• Deliver business value through iterative configuration and development.

Ontology & Data Modeling

• Design and configure ontology-driven data models aligned with business entities and processes.

• Model business domains such as:

• Quality
• Supply Chain
• Sales
• Manufacturing

• Maintain consistency in:

• Object definitions
• Relationships
• Business metrics
• Follow ontology governance standards established by the CoE.

Data Pipelines & Transformations

• Build and maintain Palantir Foundry pipelines.

• Develop data transformations using:

• Python
• PySpark
• SQL
• Work with structured and semi-structured data.

• Integrate data from multiple enterprise sources using Foundry:

• Data Connections
• Ingestion frameworks

• Optimize pipelines for:

• Performance
• Reliability
• Cost efficiency
• Support cloud-based deployments, primarily on AWS.

Business Enablement & Adoption

• Partner with:

• Product Owners
• Business Analysts
• Business Stakeholders
• Translate business requirements into configured Foundry solutions.
• Support self-service analytics and business enablement.
• Create documentation and walkthroughs for configured use cases.
• Monitor application usage and adoption.
• Use adoption insights to guide enhancements and prioritization.

Additional Responsibilities

• Design and develop end-to-end data pipelines using Palantir Foundry tools such as:

• Code Repositories
• Pipeline Builder
• Transforms
• Workshop
• Contour

• Build and maintain:

• Curated datasets
• Data lineage
• Data quality controls

• Implement data quality across:

• Ingestion
• Transformation
• Serving layers

• Implement Foundry Ontology, including:

• Objects
• Actions
• Relationships
• Enable operational workflows through ontology-driven applications.
• Develop and support Foundry dashboards and applications.
• Collaborate with stakeholders to develop data products iteratively.

• Implement security, governance, and compliance using:

• Foundry access controls
• Data policies
• Auditing practices

• Integrate Foundry with enterprise systems through:

• APIs
• Connectors
• Data interoperability patterns
• Establish CI/CD practices for Foundry Code Repositories.
• Perform peer code reviews.
• Enforce coding and development standards.
• Troubleshoot production issues and perform root-cause analysis.
• Drive continuous improvements in reliability and performance., * Palantir
• Palantir Foundry
• Palantir Core
• AWS
• Python
• PySpark
• Ontology-Based Data Modeling
• Pipeline Builder
• Foundry Transforms
• Foundry Ontology
• Workshop
• Contour

• Datasets
• Pipelines
• Ontology
• Contour
• Workshop
• Slate
• Experience with ontology-based data modeling for enterprise analytics.

• Exposure to:

• AWS cloud environments
• Distributed data systems

• Experience working in:

• Agile environments
• POD-based delivery models
• Short sprint cycles
• Business demo and feedback cycles

Good-to-Have Skills

• Experience developing business-facing dashboards and analytics for:

• Quality
• Manufacturing
• Supply Chain
• Customer Analytics

• Understanding of:

• Data governance
• Usage monitoring
• Data standardization
• Center of Excellence (CoE) practices

• Basic exposure to:

• Applied analytics
• Pattern detection

• Foundry-based analytics use cases, * Palantir Foundry

• Transforms
• Pipeline Builder
• Code Repositories
• Curated Datasets
• Data Modeling
• Foundry Ontology
• Workshop
• Contour

• Programming:

• Python - Mandatory
• PySpark - Strongly preferred

• SQL:

• Advanced SQL
• Complex joins
• Window functions
• Query optimization
• Data Governance
• Access Controls
• Data Quality
• Data Warehousing
• Dimensional Modeling
• Batch Data Processing
• Near-Real-Time Data Processing
• AWS
• APIs and Connectors
• CI/CD
• Agile

Generic Managerial Skills

• Good communication skills.
• Strong stakeholder collaboration.
• Ability to work effectively in Agile/POD-based teams.
• Ability to communicate technical concepts to business stakeholders.