Principal Data Architect

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-year cost and capability across the data estate. Interpersonal Skills Communicates complex technical concepts to executive audiences with clarity and precision. Anticipates objections, negotiates competing priorities across business units, and persuades senior internal and external stakeholders toward enterprise outcomes over local ones. # Qualifications # Required * Hands-on architecture experience with SAP Business Data Cloud (BDC), including Datasphere data modeling, replication/transformation flows, and BDC-to-lakehouse integration with platforms like Databricks * Proficiency in SAP ABAP (OO-ABAP, CDS Views, AMDP) and SQLScript/HANA-native procedures for custom extraction, transformation, and performance-tuned data logic * Working knowledge of SQL and Python for pipeline development, validation scripting, and Datasphere/Databricks transformation logic * Experience with SAP BTP extensibility (RAP, CAP) and BDC data products / Delta Sharing for building governed, reusable data services and APIs * Familiarity with SAP Analytics Cloud (SAC) or BW/BW4HANA integration, and CI/CD or transport-based version control for code-driven data models * Hands-on experience building governed Databricks data products using Unity Catalog for access control, lineage, and cross-domain data sharing * Experience designing and operating a semantic layer within Databricks (e.g., metric views, SQL warehouses, or equivalent) to serve consistent, governed metrics across BI and AI consumption tools * Technical proficiency in Databricks — Delta Lake, PySpark/Spark SQL, Delta Live Tables (or Lakeflow), and workspace/job orchestration for production-grade pipelines * Demonstrated ability to set technical direction and drive decisions across organizational boundaries without reporting authority * Bachelor's degree in Computer Science, Engineering, or related field # Preferred * Experience in semiconductor, high-tech manufacturing, or another complex global manufacturing environment * Experience architecting for AI and agentic consumption of enterprise data, including governed access patterns for AI systems * Working knowledge of data security posture management, classification, and privacy-by-design in a regulated enterprise * Experience defining technical acceptance criteria for and managing the quality of systems integrator delivery * Advanced degree in a relevant technical discipline ## Qualifications ### Education: Bachelor's Degree ### Skills ### Certifications: ### Languages: ### Years of Experience: 7 - 10 Years ### Work Experience: ## Additional Information ### ### Shift: 10-Day 8-Hr (United States of America) ### ### Travel: Yes, 10% of the Time ### ### Relocation Eligible: Yes ### Referral Payment Plan: Employee Referral (Enhanced) Salary Range: $198,000.00 - $272,500.00 The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable. For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement. Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.