below marketmost similar roles pay hereabove market
This role pays more than
63%
of similar roles. Most pay
$127,703–$223,812
— the blue band above.
At the midpoint, this role pays about
$212k
versus about
$176k
for comparable roles.
Based on 240 similar postings.
Employer
About Lam Research
Lam Research Corporation is a leading American supplier of wafer-fabrication equipment and services to the global semiconductor industry.
Lam Research currently has
137 open roles
on FindRole.
Listed pay typically runs
$114,000–$253,000
across 82 roles with salary data.
The Data Platform Architect - Palantir Foundry, Data Engineering joins the Global Information Systems Group to lead platform architecture, integration, and solution design for enterprise data, analytics, and AI use cases. You will design scalable data pipelines, develop robust Palantir Foundry Ontologies, and build end-to-end workflows to translate business needs into secure, reusable platform solutions. Key responsibilities include defining standards for modular design, data security, and performance optimization while mentoring engineering teams. You will utilize Palantir Code Repositories, Pipeline Builder, and the Ontology SDK alongside technologies such as Microsoft Fabric, Databricks, Power BI, SQL, and Python/PySpark. This role solves complex problems in data governance, semantic modeling, and lakehouse architecture to support operational readiness across supply chain, manufacturing, and service systems.
Design and architect scalable data pipelines in Palantir Foundry for enterprise data ingestion and transformation.
Develop and maintain Palantir Foundry Ontologies to model business entities and operational workflows.
Build end-to-end data workflows using Palantir Code Repositories, Pipeline Builder, and Python/PySpark.
Implement Palantir native capabilities for data lineage, governance, and secure access controls.
Define standards for modular design, performance optimization, and scalable deployment within the Palantir ecosystem.
Mentor engineering teams on consistent engineering practices and evaluate emerging technologies for AI enablement.
Partner with stakeholders to define solution roadmaps and deliver governed, operationalized data solutions.
What we're looking for
12+ years of experience in data architecture, platform engineering, cloud data platforms, analytics, digital transformation, or enterprise data modernization initiatives.
Deep expertise in Palantir Foundry, Ontology, Pipeline Builder, Code Repositories, Operational Applications, Ontology SDK, data lineage, governance, and platform administration.
Strong experience with modern data platforms such as Palantir, Microsoft Fabric, Databricks, Snowflake, Azure Synapse, or equivalent cloud-native analytics ecosystems.
Strong understanding of Palantir ontology modeling, lakehouse architecture, data warehousing, semantic modeling, enterprise integration patterns, and operational analytics.
Hands-on experience with Palantir Foundry security and governance frameworks, SQL, data modeling, ETL/ELT, Python/PySpark, and enterprise analytics solutions.
Strong understanding of data governance, Lifecycle, metadata, lineage, access control, and data quality frameworks.
Strong communication skills and ability to lead business-facing discussions and translate business problems into scalable technical solutions.
Bachelor’s degree in Computer Science, Information Technology, MIS, Data Science, Analytics, or a relevant Engineering field (Master's or PhD preferred).
Experience with SAP, MES, Kinaxis, supply chain, planning, manufacturing, service systems, APIs, or operational databases (preferred).