Lead Data Engineer

Lam Research • Fremont, CA

20h • Hybrid

About The Position

In this role, you will directly contribute to Lam’s Enterprise AI strategy by building the scalable, AI-ready data foundation that powers generative AI, machine learning, and advanced analytics across the company. You will define and deliver modern data architecture, trusted data products, and production-grade data pipelines that enable Enterprise AI use cases at scale.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or a related field.
• 8+ years of experience in data engineering, data architecture, platform engineering, or related technical roles.
• Strong hands-on experience designing and building cloud-based data solutions on Microsoft Azure.
• Strong proficiency in Python, SQL, and Spark for data transformation, pipeline development, and large-scale data processing.
• Experience with modern data architecture patterns, including Lakehouse and Medallion architecture, and building production-grade data pipelines that integrate data from multiple enterprise systems.
• Experience partnering with cross-functional teams to deliver scalable technical solutions that support business and platform goals.

Nice To Haves

• Experience with Microsoft Fabric, Azure Databricks, Azure Data Factory, Synapse, or related Azure data services.
• Experience supporting AI/ML or generative AI use cases, including data preparation for model training, inference, vector search, or Retrieval-Augmented Generation (RAG) workflows.
• Experience with graph data models, knowledge graph technologies, or graph databases such as Neo4j.
• Experience with Azure AI Search, event-driven ingestion patterns, CI/CD for data engineering, and monitoring or observability practices for data platforms.

Responsibilities

• Architect and build scalable, production-grade data pipelines and data products on Azure, Microsoft Fabric, and related cloud data platforms to support Enterprise AI use cases.
• Design and implement data architecture patterns, including Medallion architecture and curated data layers, to improve data quality, usability, and governance for AI and analytics workloads.
• Develop and optimize large-scale data processing solutions using Python, SQL, Spark, and modern Azure data services to support high-volume, high-performance workloads.
• Build AI-ready data assets for machine learning and generative AI applications, including vector search, Retrieval-Augmented Generation (RAG), graph-based use cases, and semantic data models.
• Partner closely with AI/ML engineers, data scientists, business teams, and platform teams to translate AI use-case requirements into scalable, governed, and production-ready data solutions.
• Drive architecture decisions for data integration, storage, transformation, and serving layers that support the long-term Enterprise AI roadmap.
• Contribute to engineering quality through CI/CD, automation, observability, and operational readiness practices for data pipelines and platforms.
• Document architecture decisions, technical designs, and operating procedures to support maintainability, operational readiness, and long-term platform sustainability.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees