This role pays more than
75%
of similar roles. Most pay
$142,400–$211,625
— the shaded band above.
At the midpoint, this role pays about
$212k
versus about
$177k
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
299 open roles
on FindRole.
Listed pay typically runs
$114,000–$253,000
across 141 roles with salary data.
Data Architect
As part of the Global Information Systems Group, the Data Architect will drive the data architecture and engineering agenda for the Customer Support and Service organization's Digital Transformation program. This role involves designing the end-to-end data landscape, including data models, pipelines, and integration patterns to unify service, installed-base, field operations, and customer engagement data into analytics and AI ready products. The candidate will author technical specifications, design scalable cloud data platforms, and serve as a technical advisor for complex cross-functional solutions. Key technologies include the Azure tech stack, MS Fabric, Power BI, Spark, Python, Databricks, Snowflake, SQL, and ETL tools like Fivetran, Kafka, or ADF. The role addresses challenges in IoT and enterprise data domains, specifically integrating telemetry from installed-base equipment with platforms like SAP and MS Dynamics to create robust, high-quality data products.
Define and document target-state data architecture including source-to-target mappings and canonical data models.
Author technical specifications and solution designs to guide development teams through implementation.
Architect scalable, secure, and cost-efficient data pipelines across enterprise service systems.
Serve as a technical advisor to business and development teams on analytics design for complex solutions.
Ensure all solutions align with Data COE principles, architectural standards, and governance policies.
Design advanced Analytics and AI applications using the Azure tech stack, MS Fabric, and Power BI.
Sequence the project roadmap and resolve design trade-offs with stakeholders and delivery teams.
What we're looking for
12+ years of experience in modern data engineering, warehousing, or data lakes on cloud platforms like Azure Synapse, MS Fabric, Databricks, or Snowflake.
5 years of hands-on experience using Spark and Python technologies for big data processing.
3 years of experience implementing end-to-end medallion architecture using Databricks or other cloud tools.
5+ years of experience with ETL/ELT tools such as Fivetran, Kafka, or Azure Data Factory for real-time, streaming, and batch ingestion.
8+ years of SQL experience in cloud native data warehousing tools including data modeling.
Proven experience in schema design and dimensional data modeling.
Working knowledge of service and customer platforms like SAP and MS Dynamics, plus IoT/telemetry data.
Experience communicating insights to influence executives and colleagues.
Data Modeling
SQL
Python
AWS
S3
Glue
Redshift
Athena
Lake Formation
ETL
ELT
Data Governance
Data Quality
Metadata Management
Data Cataloging
Lineage
Agile
Data Architecture
Python
SQL
AWS
S3
Glue
Redshift
Athena
Lake Formation
dbt
Airflow
ETL
ELT
Data Modeling
Data Governance
Metadata Management
Data Cataloging
Agile
Python
SQL
AWS
Azure
Apache Spark
Apache Kafka
Data Warehousing
Data Lake
Lakehouse
MLOps
ETL
ELT
Scala
Java
Data Mesh
Medallion Architecture
Big Data
Agile Methodology
GenAI
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