A

Applied Materials

Builds equipment for chip and display factories

Principal Data Architect

Data ManagementConfirmed live in the last 24 hours
Full-timeSanta Clara, CA, USAIn-person

About the Job

Requirements

  • Hands-on architecture experience with SAP Business Data Cloud (BDC), including Datasphere data modeling, replication and transformation flows, and BDC-to-lakehouse integration with platforms such as 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, such as metric views, SQL warehouses, or equivalent, to serve consistent, governed metrics across BI and AI consumption tools.
  • Technical proficiency in Databricks, including 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 a related field.

Responsibilities

  • Define and own the target-state architecture for Applied's data platform and BI landscape; establish reference architectures, design patterns, and best known methods for integrated solution design; serve as architecture approver for platform and solution designs, with authority to require rework when designs diverge from enterprise standards.
  • Provide end-to-end technical leadership for complex, multi-year, multi-business-unit data transformation programs, covering current-state assessment, target architecture, migration strategy, sequencing, cutover design, and decommissioning; own architecture-level risks and dependencies that cross program boundaries.
  • Act as the data architecture authority to the S/4 program; own the data model and master data implications of ERP design decisions, conversion and harmonization strategy for legacy and historical data, and downstream architecture that makes S/4 data consumable for analytics and AI; ensure ERP decisions account for downstream cost.
  • Define and own the data product operating model, including product definition, data contracts, ownership, certification criteria, quality and freshness service-level agreements, versioning, and deprecation; directly architect the highest-impact enterprise data products and certify others; drive reuse to reduce the overall asset footprint.
  • Own the design and governance of the enterprise semantic layer, including common business vocabulary, conformed dimensions, and certified metric definitions; architect it to serve BI, self-service, embedded analytics, and agentic AI from a single governed definition set; establish change control for semantic definitions.
  • Embed governance into architecture through catalog and lineage coverage, classification, attribute- and role-based access control, and data quality instrumentation as design-time requirements; partner with Information Security and Compliance on data protection posture, encryption and key management design, and SOX-relevant controls within the data estate.
  • 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; recommend changes to enterprise architectural strategy; serve as senior technical counterpart to strategic vendors and partners.
  • 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 against them; escalate quality and capability concerns to accountable delivery managers.
  • 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 established patterns.
  • Translate architectural tradeoffs into business terms for senior stakeholders, including cost, risk, time-to-value, and optionality; build the case for architecture investment and drive alignment across business-unit leaders whose local priorities conflict with the enterprise target state.

Desired Qualifications

  • 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.

About the Company

Applied Materials

Builds equipment for chip and display factories

Applied Materials designs and builds precision machines that chipmakers and display manufacturers use to form, shape and inspect thin layers of material. Its platforms handle steps such as depositing films and removing unwanted material, helping chipmakers create transistors and wiring at atomic scale. Customers include makers of logic chips and memory, as well as manufacturers of advanced displays. The company earns money from equipment sales, replacement parts and services, and factory software that schedules production and monitors manufacturing processes. Applied Materials was founded in 1967 and is headquartered in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1967

Recently Posted Jobs

Explore more opportunities at Applied Materials

See more jobs