Programmer Lead - Enterprise Analytics

Support and implement scalable data pipelines in Palantir Foundry, enabling seamless ingestion, transformation, and delivery of data across enterprise systems. Develop and maintain robust Palantir Foundry Ontologies to model business entities, relationships, and operational workflows for enhanced data usability and decision-making. Build and support data workflows leveraging Palantir Code Repositories, Pipeline Builder, and operational applications while integrating with Microsoft Fabric, Databricks, Power BI, SQL, Python/PySpark, and cloud data services. Leverage Palantir native capabilities such as Foundry Ontology SDK, data lineage, governance, and access controls to deliver secure, reusable, and production-grade data assets. Implement best practices for modular design, data security, access management, performance optimization, testing, and scalable deployment within the Palantir ecosystem. Enhance data security and optimize Palantir Foundry data pipelines, transformations, queries, and storage architectures to improve platform performance and reliability. Support CI/CD, version control, deployment automation, and release management. Collaborate with cross function and onsite/offshore teams to meet delivery, quality, and support expectations. 6+ years of experience in data architecture, platform engineering, cloud data platforms, analytics, digital transformation, or enterprise data modernization initiatives. Understanding of Palantir Foundry, Ontology, Pipeline Builder, Code Repositories, Operational Applications, Ontology SDK, data lineage, governance, and platform administration. Experience with modern data platforms such as Palantir, Microsoft Fabric, Databricks, Snowflake, Azure Synapse, or equivalent cloud-native analytics ecosystems. Hands-on experience implementing data security, access controls, data modeling, SQL, ETL/ELT pipelines, Python/PySpark, and analytical solutions within the Palantir Foundry stack. Experience building pipelines, lakehouse layers, warehouse objects, semantic datasets, and analytical models. Experience with SAP, manufacturing, supply chain, planning, service, logistics, inventory, quality, finance, or operational systems is preferred. Experience with Azure DevOps, Git, CI/CD, deployment automation, monitoring, and production support. Understanding of governance, access control, metadata, lineage, cataloging, certification, and data quality. Bachelor's degree in Computer Science, IT, Data Science, Analytics, Engineering, or related field. Our commitment We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees. Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. ‘On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.