Principal Data Architect

Who We Are

Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.

What We Offer

Salary:

$198,000.00 - $272,500.00

Location:

Santa Clara,CA

You’ll 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.

At Applied Materials, we care about the health and wellbeing of our employees. 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 .

As a Software Engineer at Applied Materials, you’ll dive deep into ground-breaking technologies—like machine learning and AI—to craft novel software solutions that solve our customers’ high-value problems. Our Software Engineers are responsible for designing, prototyping, developing, and debugging software solutions for semiconductor equipment components and devices to ensure quality and functionality. You'll develop software documentation and test procedures, troubleshoot software problems, and communicate with internal customers to understand project requirements. As part of our team, you'll contribute your expertise in intricate systems, deciphering code, and anticipating software behaviors to ensure Applied remains the leader in the semiconductor and display sectors.

The Principal Data Architect serves as the senior technical authority for Applied's enterprise data architecture, accountable for the coherence of the data landscape across large-scale transformation programs. Owns the architecture of certified data products and the enterprise semantic layer, provides data architecture leadership to the S/4 transformation, and sets the standards, patterns, and decision gates that delivery teams and partners build against. Operates through technical credibility and influence across business units rather than through direct reporting authority.

Key Responsibilities:

Enterprise data architecture and standards. Define and own the target-state architecture for Applied's data platform and BI landscape. Establish reference architectures, design patterns, and BKMs for integrated solution design. Serve as architecture approver for platform and solution designs, with authority to require rework where designs diverge from enterprise standards.

• •Large-scale data transformation leadership. Provide end-to-end technical leadership for complex, multi-year, multi-BU data transformation programs — current-state assessment, target architecture, migration strategy, sequencing, cutover design, and decommissioning. Own the architecture-level risks and dependencies that cross program boundaries and would otherwise fall between program owners.
• •S/4 data transformation. Act as the data architecture authority to the S/4 program. Own the data model and master data implications of ERP design decisions, the conversion and harmonization strategy for legacy and historical data, and the downstream architecture that makes S/4 data consumable for analytics and AI. Ensure ERP-side decisions are made with full visibility into their downstream cost.
• •Data products development. Define and own the data product operating model — product definition, data contracts, ownership, certification criteria, quality and freshness SLAs, versioning, and deprecation. Architect the highest-impact enterprise data products directly and certify the rest. Drive reuse so that data products reduce the overall asset footprint rather than adding to it.
• •Enterprise semantic layer. Own the design and governance of the enterprise semantic layer — the common business vocabulary, conformed dimensions, and certified metric definitions that guarantee a measure means the same thing in every consuming tool. Architect the layer to serve BI, self-service, embedded analytics, and agentic AI consumption from a single governed definition set. Establish the change-control process for semantic definitions.
• •Governance, security, and quality by design. Embed governance into the architecture rather than retrofitting it: catalog and lineage coverage, classification, attribute- and role-based access control, and data quality instrumentation as architectural requirements at design time. Partner with Information Security and Compliance on data protection posture, encryption and key management design, and SOX-relevant controls within the data estate.
• •Technology strategy and vendor assessment. Own multi-year platform and capability roadmaps for the data and BI estate. Lead technical evaluation of vendor products and next-generation technologies, including proof-of-concept design and objective scoring. Assess architectural lock-in and exit cost as a first-class criterion. Recommend additions and changes to Applied's enterprise architectural strategy. Serve as senior technical counterpart to strategic vendor and partner relationships.
• •Technical direction of delivery and partner teams. Set and enforce technical direction for internal delivery teams, systems integrators, and contingent technical staff through design reviews, architecture gates, and code and model review. Define technical acceptance criteria for partner statements of work and assess delivered work product against them. Escalate quality and capability concerns to the accountable delivery managers.
• •Technical community leadership. Raise the architectural and data modeling capability of the broader data organization through mentoring, design review, internal standards documentation, and targeted enablement. Build the bench of engineers and architects capable of extending the patterns this role establishes.
• •Executive influence and decision support. Translate architectural tradeoffs into business terms for senior stakeholders — cost, risk, time-to-value, optionality. Build the case for architecture investment and drive alignment across BU leaders whose local optima conflict with the enterprise target state.

Competency Framework:

Functional Knowledge Recognized as the enterprise technical authority in data architecture and an advanced expert within the data and analytics discipline. Maintains deep, current knowledge of adjacent disciplines including ERP data, information security, and AI/ML platform engineering.

Business Expertise Applies in-depth understanding of how data architecture integrates across the segment and function, and of the commercial and operational drivers of the business units the data estate serves. Anticipates the business consequences of architectural decisions.

Leadership Leads programs of substantial complexity, risk, and organizational breadth without formal reporting authority. Sets technical direction for multiple delivery teams and partner organizations, establishes the standards others execute against, and mentors senior technical staff.

Problem Solving Solves unique and ambiguous problems with broad enterprise impact where no established precedent exists. Requires conceptual and innovative thinking, and the judgment to distinguish problems that need a novel solution from those that need an existing standard applied consistently.

Impact Impacts the direction, sequencing, and resource allocation of enterprise programs, platforms, and technology investments. Architectural decisions made in this role determine multi-