Lead Data Engineer

Lam Research

Hybrid

Quick summary

Work type
Hybrid
Location
Fremont, CA
Salary
$141,000–$307,000 / yr
Posted
46 days ago
Closes
Oct 17, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $181k
This role $224k
$121k most similar roles pay here $327k

This role pays more than 80% of similar roles. Most pay $146,037–$216,656 — the shaded band above. At the midpoint, this role pays about $224k versus about $181k 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 267 open roles on FindRole.

Listed pay typically runs $114,000–$231,000 across 132 roles with salary data.

Most-posted roles

View all roles at Lam Research

At a glance

TL;DR · Lead Data Engineer

As a Senior Data Architect at Lam’s Enterprise AI team, you will play a pivotal role in establishing the scalable data foundation that drives generative AI, machine learning, and advanced analytics across the organization. Your responsibilities include architecting and implementing production-grade data pipelines on Azure and Microsoft Fabric, designing robust data architecture patterns to enhance data quality and governance, and developing large-scale data processing solutions using Python, SQL, Spark, and modern cloud services. You will collaborate closely with AI/ML engineers, data scientists, and business teams to build AI-ready data assets for machine learning applications, ensuring seamless integration of data from multiple enterprise systems. Additionally, you will contribute to the long-term Enterprise AI roadmap by driving architecture decisions and maintaining operational readiness through CI/CD practices and documentation.

What you'll do

  • Architect scalable, production-grade data pipelines on Azure and Microsoft Fabric.
  • Design modern data architecture patterns to enhance data quality and governance.
  • Develop large-scale data processing solutions using Python, SQL, Spark, and Azure services.
  • Build AI-ready data assets for machine learning and generative AI applications.
  • Drive long-term Enterprise AI roadmap through strategic data integration and storage decisions.
  • Contribute to engineering quality by implementing CI/CD, automation, and observability practices.

What we're looking for

  • 8+ years of experience in data engineering or related technical roles.
  • Strong hands-on expertise in designing cloud-based data solutions on Microsoft Azure.
  • Proficiency in Python, SQL, and Spark for large-scale data processing and pipeline development.
  • Experience with modern data architecture patterns like Lakehouse and Medallion architecture.
  • Expertise in supporting AI/ML use cases including vector search and Retrieval-Augmented Generation (RAG).
  • Knowledge of graph data models and related technologies such as Neo4j.

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