Data Architect - Enterprise Analytics

Global Information Systems

As a Data Architect, you will design and deliver scalable, governed, and AI-ready enterprise data solutions that support analytics, digital transformation, and emerging AI use cases. You will provide technical leadership across data architecture, modeling, integration, engineering, semantic modeling, and data product design while translating complex business requirements into trusted and reusable enterprise data capabilities.

• Define and evolve enterprise data architecture, reference architectures, standards, patterns, and technology roadmaps.
• Design conceptual, logical, physical, dimensional, canonical, and semantic data models representing complex business entities, relationships, and processes.
• Architect scalable data integration and ingestion patterns using batch, near-real-time, streaming, APIs, and event-driven approaches.
• Design modern lakehouse, data warehouse, medallion, semantic-layer, and data-product architectures using platforms such as Microsoft Fabric, Databricks, Azure, and related technologies.
• Create AI-ready data foundations by ensuring enterprise data is well modeled, contextualized, governed, discoverable, secure, and optimized for downstream consumption.
• Define reusable architecture and engineering patterns for data ingestion, transformation, storage, integration, and delivery.
• Establish standards for data quality, metadata, lineage, security, access control, observability, performance, and lifecycle management.
• Partner with business SMEs, application teams, data engineers, analytics teams, and solution architects to translate business needs into scalable technical solutions.
• Lead architecture and design reviews, provide hands-on technical guidance, and help engineering teams resolve complex data and integration challenges.
• Evaluate emerging data technologies and architecture patterns and recommend solutions aligned with enterprise strategy.

• 10+ years of experience in data architecture, data engineering, enterprise data platforms, data warehousing, or related technology roles.
• Deep expertise in enterprise data modeling and a strong understanding of modern data architecture principles and design patterns.
• Strong hands-on technical skills with SQL, Python/PySpark, Spark, ETL/ELT, APIs, and distributed data processing.
• Strong experience with modern cloud data platforms such as Microsoft Fabric, Databricks, Azure, Snowflake, or equivalent technologies.
• Proven experience architecting and delivering large-scale enterprise data solutions from source through consumption.
• Experience integrating complex enterprise platforms and data sources such as SAP, MES, PLM, IoT, APIs, files, and operational databases.
• Strong understanding of data governance, quality, metadata, lineage, security, and access management.
• Ability to balance strategic architecture with hands-on technical problem-solving, working effectively with architects, engineers, application teams, and business stakeholders.
• Strong communication skills with the ability to explain complex data architecture concepts to both technical and business audiences.
• Highly motivated self-starter and continuous learner who thrives in a fast-paced, dynamic environment, takes end-to-end ownership, and brings a strong “let’s get this done” mindset to solving complex data challenges.

• Experience with manufacturing, semiconductor, engineering, equipment, IoT, or other complex operational data environments.
• Experience designing enterprise semantic models, reusable data products, and common data domains.
• Understanding of how enterprise data architecture and semantic/contextual data models enable AI-ready data consumption.
• Experience with real-time/streaming architectures, event-driven integration, and large-scale data processing.
• Experience with CI/CD, automated testing, monitoring, and production engineering practices for enterprise data solutions.
• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Data Science, Engineering, or related discipline. Master’s degree preferred.

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.

Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.