Palantir Foundry Developer (Applications & Data Ingestion)

About the Role
We're looking for a developer experienced with Palantir Foundry to build user-facing applications and robust data ingestion pipelines that power analytics and operations. You'll partner with data engineers, product owners, and business stakeholders to translate requirements into secure, scalable solutions using Foundry's Ontology, Pipelines, Code Workbooks/Repositories, and Operational Applications (e.g., Objects & Actions driven workflows).

What You'll Do
Application Development (Foundry)

• Design and implement Foundry applications leveraging the Ontology (Objects, Object Types, Actions) to model real-world business entities and operational workflows.
• Build user experiences that enable analysts and operators to act on data (e.g., approve/resolve flows, exception handling, operational dashboards, write-back workflows).
• Implement Actions with authorization policies and validations; integrate with downstream systems/APIs when needed.
• Create reusable components and templates to accelerate future app builds.
• Partner with product and UX to define acceptance criteria and instrument telemetry/usage analytics.

Data Ingestion & Transformation

• Build and maintain Foundry Pipelines (graph-based and/or code-based) for batch and streaming ingestion from sources such as REST APIs, S3 buckets, AWS/cloud databases, message queues.
• Implement schema management, data quality checks, lineage, and observability across ingestion layers.
• Use Code Workbooks / Foundry Repositories (e.g., PySpark, SQL, and Python tooling available in Foundry) to develop transformations, validations, and feature tables.
• Optimize performance (partitioning, caching, parallelization) and manage cost/throughput at scale.
• Establish robust CDC (Change Data Capture), incremental loads, and idempotent reprocessing patterns.

Security, Governance, and Reliability

• Apply Foundry's governance model: access controls, Row/Column-Level Security, and purpose-based permissions aligned with data contracts.
• Ensure compliance with organizational standards (PII handling, retention, and audit).
• Implement monitoring/alerting, SLAs/SLOs, and runbooks for data products and apps.

Collaboration & Delivery

• Translate business requirements into technical designs and iterate quickly with stakeholders.
• Use Git-based workflows (branching, PRs, code reviews) within Foundry.
• Document solutions (tech specs, runbooks, user guides) and run enablement sessions.

Required Qualifications

• 3 6+ years of professional experience in data/application development; 2+ years hands-on with Palantir Foundry.
• Strong knowledge of Foundry Ontology (Objects, Properties, Actions, Interactions) and building Operational Applications on top of it.
• Proficiency with Foundry Pipelines and Code Workbooks/Repositories using PySpark and SQL (and/or Scala/Spark).
• Experience designing ingestion patterns (batch, micro-batch, streaming), quality checks, and lineage.
• Solid software engineering practices: testing, CI/CD, code reviews, version control.
• Familiarity with APIs and integrations (REST/GraphQL), and messaging/queues where applicable.
• Strong communication skills and ability to collaborate with non-technical stakeholders.

Preferred Qualifications

• Experience with data masking, and compliance controls in Foundry.
• Background with data modeling and semantic layers; designing scalable Ontology models.
• Exposure to ML/feature engineering in Foundry or integration with external ML platforms.
• Cloud fluency (AWS/Azure/GCP), object storage, and network connectivity patterns.
• Domain experience (e.g., Life Sciences, healthcare, manufacturing) is a plus.

Tools & Stack You May Use Here

• Palantir Foundry: Ontology, Objects & Actions, Pipelines, Code Workbooks/Repositories, Data Lineage & Governance
• Languages: Python, PySpark, SQL (Scala optional)
• Versioning/CI: Git (PR reviews, testing, CI/CD in Foundry)
• Monitoring: Foundry lineage/health, logs, alerting; complementary APM/observability tools
• Data Sources: REST APIs, JDBC/ODBC, S3, Kafka/Streams (as applicable)