This role pays more than
78%
of similar roles. Most pay
$142,400–$208,680
— the shaded 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
314 open roles
on FindRole.
Listed pay typically runs
$114,000–$242,000
across 158 roles with salary data.
Data Architect
The Data Architect joins the Global Information Systems team to drive digital transformation by designing and developing data engineering and integration solutions for future systems. This role involves drafting specifications, creating solution designs, and collaborating with business and development groups to ensure alignment with data hub principles. The individual will build scalable data architectures, develop governance specifications, and create ETL/ELT pipelines to support enterprise decision-making. Key responsibilities include managing big data platform initiatives and providing guidance on emerging analytics trends. The role requires expertise in SQL, Spark, Python, and dimensional data modeling. Technical requirements include experience with Azure, AWS, Databricks, Microsoft Fabric, Synapse, Power BI, and Redshift. The position focuses on solving complex analytics design problems by integrating platforms like Workday Adaptive into the cloud-native stack to support financial planning and large dataset analysis in IoT and enterprise domains.
Design and develop data engineering solutions and governance specifications for digital transformation projects.
Create solution designs and technical specifications for cloud-native big data platforms.
Build ETL/ELT pipelines to integrate Workday Adaptive with the Azure analytics stack including Microsoft Fabric and Power BI.
Lead the design of scalable data and analytics architectures during business transformation workshops.
Advise business teams on complex analytics designs while ensuring alignment with corporate data standards.
Develop and advocate for advanced analytics standards across the organization's Data Hub.
Demonstrate technical capabilities and proof-of-concept projects to showcase the potential of the Data Fabric platform.
What we're looking for
Bachelor's degree in Computer Science, Information Technology, MIS, Data Science, Analytics, or a relevant Engineering field; Master's or PhD (preferred).
Over 12 years of experience with modern data engineering, data warehousing, and data lake technologies on cloud platforms like Azure, AWS, and Databricks.
Over 10 years of SQL experience with cloud-native data warehousing and data modeling.
Over 5 years of experience building and supporting FP&A applications integrated with ERP systems and Azure data platforms.
Over 5 years of experience configuring Azure cloud/SaaS platforms and building automated ETL/ELT pipelines for real-time, streaming, and batch data exchange.
At least 3 years of experience working with Spark and Python technologies for big data processing.
At least 3 years of hands-on experience implementing end-to-end medallion architecture using Databricks or similar cloud tools.
Proven background in schema design, dimensional data modeling, and knowledge of data warehouse best practices on platforms like MS Fabric or Azure Synapse.
Data Architecture
PostgreSQL
AWS
SQL
Data Modeling
Data Governance
DataOps
Time-Series Data
Big Data
Machine Learning
AI
Data Warehousing
Data Engineering
Metadata Management
Distributed Query Engines