About the Role
We are seeking an experienced Data Engineer with strong, hands-on expertise in Palantir Foundry to design, build, and optimize scalable data pipelines, semantic models, and data products.
In this role, you will collaborate closely with data scientists, analysts, product teams, and business stakeholders to deliver robust, production-grade data foundations that enable analytics, automation, and operational decision-making. You will play a key role in shaping our data ecosystem, with a strong focus on reliability, performance, scalability, data quality, and long-term sustainability .
Experience Requirement: 5+ years in Data Engineering, including 1-2 years of strong hands-on Palantir Foundry experience.
Key Responsibilities
- Design, develop, and maintain end-to-end data pipelines using Palantir Foundry , including Pipeline Builder, Code Repositories, Data Lineage, Ontology, Workshop, Quiver, and related Foundry capabilities.
- Implement batch, incremental, and streaming ETL/ELT workflows using reusable, scalable, and production-ready components.
- Build and maintain high-quality, version-controlled data products aligned with business and analytical requirements.
- Work across federated data environments , integrating diverse data sources and addressing complex data integration challenges.
- Design, extend, and maintain Foundry Ontologies , including object types, link types, property types, and semantic relationships.
- Develop semantic data layers that support analytics, operational workflows, automation, and machine learning use cases .
- Establish and enforce strong data quality practices through validation, lineage, monitoring, and governance frameworks.
- Monitor and optimize pipeline performance for scalability, reliability, cost efficiency, and processing speed .
- Implement automated testing, CI/CD workflows, Git-based development practices, and deployment best practices for Foundry data assets.
- Troubleshoot production issues, perform root-cause analysis, and implement sustainable long‑term solutions.
- Translate ambiguous business requirements into scalable, maintainable, and production-ready data engineering solutions.
- Support Foundry Workshop applications, dashboards, and end‑user analytical experiences .
- Collaborate effectively with technical and non‑technical stakeholders and communicate data architecture, pipeline behavior, dependencies, and limitations clearly.
Required Qualifications
- Bachelor's or master's degree in Computer Science, Engineering, Information Systems, or a related field .
- 5+ years of professional experience in Data Engineering, including 1-2 years of strong hands‑on Palantir Foundry experience.
- Proven experience working with Palantir Foundry in a production environment .
- Strong proficiency in Python, SQL, PySpark, and Spark SQL .
- Experience delivering production‑grade data pipelines in AWS, Azure, or GCP .
- Strong understanding of data modelling, schema design, metadata management, data quality, and governance .
- Familiarity with CI/CD, Git‑based workflows, automated testing, and software engineering best practices .
- Strong problem‑solving and troubleshooting skills, with the ability to work effectively in complex data environments.
- Excellent communication and collaboration skills, with the ability to work across engineering, analytics, product, and business teams.
Preferred/Nice‑to‑Have Skills
- Experience building and maintaining Foundry Ontologies and semantic models .
- Experience with Foundry Workshop, Quiver, Actions, and operational workflows .
- Experience with streaming data architectures and Real Time data processing.
- Experience implementing data governance, observability, and data quality frameworks.
- Familiarity with machine learning data pipelines and ML‑oriented data products.
- Experience working in large‑scale, federated, or enterprise data environments.
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