Data Engineer 4

In your career, let’s prove what’s possible.

At Lam Research, we create equipmentthat drives technological advancements in the semiconductor industry. Our innovative solutions enable chipmakers to power progress in nearly all aspects of modern life, and it takes each member of our team to make it possible.

Across our organization, our employees come to work and change the world. We take on the toughest challenges with precision and accuracy. We push for the next big semiconductor breakthrough. We lead the way in one of the most critical and fast-moving industries on the planet. And we do it together, with deep connections and limitless collaboration.

The impact we have on the world is made possible by focusing on our people. So we recognize and celebrate our teams’ achievements. We strive to create an inclusive and diverse culture where everyone’s contribution and voice has value. We evaluate and evolve our offerings, so our people receive the support and empowerment to do meaningful things for their lives, careers, and communities.

Because at Lam, we believe that when people are the priority and they’re inspired to unleash the power of innovation for a better world together, anything is possible.

Date:
Jul 16, 2026

Location:

Fremont, CA, US, 94538

Worker Category:
On-site Flex

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.

• 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.

Minimum Qualifications:

• 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.

• 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…