Senior Data Architect

Who We Are

Applied Materials is the global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to work beyond the cutting-edge, continuously pushing the boundaries of science and engineering to make possible the next generations of technology, join us to Make Possible® a Better Future. 

What We Offer

Salary:

$148,000.00 - $203,500.00

Location:

Austin,TX, Santa Clara,CA

At Applied, we prioritize the well-being of you and your family and encourage you to bring your best self to work. Your happiness, health, and resiliency are at the core of our benefits and wellness programs. Our robust total rewards package makes it easier to take care of your whole self and your whole family. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits. 

You’ll also benefit from a supportive work culture that encourages you to learn, develop and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more about careers at Applied.

Job Summary

Consistently ranked among Computerworld’s 100 Best Places to Work in IT, Applied Material’s Global Information Services (GIS) organization offers an exciting place for its employees to succeed.  We are seeking a strategic and technically skilled Senior Data Architect to lead the design and implementation of scalable, high-performance data architectures supporting critical operations and strategic data initiatives across Applied Materials data ecosystems —from R&D to supply chain, customer delivery and services. This role will work cross-functionally to advance data management practices, ensure data quality and governance, and enable analytics and AI/ML capabilities across the enterprise.

Key Responsibilities

• Design and maintain a robust, secure, and scalable data architecture aligned with enterprise and digital transformation strategies.

• Define conceptual, logical and physical data models for structured and unstructured data from enterprise systems to support research, metrology, labs, ERP, MES, finance, corporate, PLM, and IoT systems.

• Architect, and identify data and process standardization opportunities with data across labs, research, design tools, manufacturing facilities, supply chain systems, finance systems, manufacturing systems, ERP, PLM, home grown applications and external partners.

• Enable data governance practices for critical business data to ensure metadata management, master data consistency, lineage tracking, and compliance with SEMI and industry regulations.

• Partner with application and enterprise architecture teams with the adoption of modern cloud-based data platforms (e.g., Databricks, Azure) and big data technologies to support analytics, AI/ML use cases.

• Collaborate with data engineers, business analysts, data scientists, enterprise architects, domain SMEs, and operational teams to understand requirements and translate them into data architecture strategies.

• Establish data architecture frameworks, standards, and policies tailored to the semiconductor domain’s complexities and scale.

Qualifications

Education:

• Bachelor’s or Master’s degree in computer science, Information systems, or a related field.

Experience:

• 8–12 years of experience in enterprise data architecture, preferably within semiconductor, electronics, or manufacturing domains.

• Preferred experience with Semi industry-specific systems

• Knowledge of semiconductor processes, manufacturing, supply chain, and data-intensive engineering environments.

Technical Skills:

• Must have string expertise in data architecture and modeling (relational, NoSQL)

• Must be proficient in big data and modern data platforms: Databricks, Hadoop

• Understanding with ETL/ELT tools like Informatica or DataStage

• Experience with enterprise reporting tools, Tableau, PowerBI.

• Familiarity with SAP systems and integration strateg