Data Application Engineer, Enterprise Data Management

We are inviting a highly motivated and experienced Enterprise Data Management – Data Application Engineer (Supply Chain) to join our Business Applications group. This function plays a vital role in our mission to transform computing by leading the creation, oversight, and advancement of enterprise data platforms and global business workflows. As a professional specializing in enterprise data management, supply chain operations, data architecture/platforms, and Agentic AI, you will partner with business contacts and IT teams to offer scalable, resilient, and future-ready data solutions. Your understanding of supply chain operations will contribute to resolving complex issues, refining data governance and observability, and ensuring trusted, high-quality information across the supply network. What You’ll Be Doing: • Develop an in-depth understanding of the entire chip supply chain, including chip family and part development, PLM system input/output/yield correlations, ECC/Z-flow material master configuration and growth, along with NVIDIA’s planning master data (BOM, Routing, Production Version), and the ontology/knowledge graph structure supporting EDM’s agentic AI projects. • Develop, test, and maintain data pipelines, APIs, and agent integrations for the Planning Data Management Tool (PDMT) and related chips and boards planning data solutions, supporting critical supply chain functions. • Architect and implement enterprise Master Data Management (MDM) and Reference Data Management (RDM) solutions for material master, BOM, customer, supplier, and reference data within the supply chain. • Collaborate closely with engineering, business, and IT groups to transform complex supply chain and semiconductor requirements into scalable, governed, and business-aligned data solutions. • Design and implement data integration and pipeline architectures, including real-time, batch, web-based, and event-based pipelines for large-scale manufacturing and supply chain datasets. • Lead the creation of enterprise data governance capabilities, encompassing business glossaries, data catalogs, lineage tracking, and stewardship frameworks aligned with multi-functional business processes. • Establish an AI-enabled data observability layer to proactively monitor data quality, lineage, and operational health across data domains. • Build and manage enterprise-grade AI agents supporting EDM data observability. Automate workflows across data processing streams. Enable self-healing of data from various sources, including SAP systems and other business applications. • Develop canonical data models, standardized taxonomies, and process-aligned data structures to ensure consistent, reusable, and interoperable enterprise data. What We Need to See: • More than 8 years of experience in enterprise data architecture and engineering, MDM, RDM, and scalable data platform solutions—ideally in comprehensive supply chain or semiconductor manufacturing environments. The ideal candidate is a hands-on data application engineer assisting a senior EDM architect. • Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, Industrial Engineering, or equivalent experience in enterprise data architecture and data platform implementations. • Hands-on expertise with Informatica Intelligent Data Management Cloud (IDMC), including MDM, CDI, CAI, CDGC, IDQ, Reference 360, Metadata Management, and Data Catalog capabilities. • Extensive experience with Databricks lakehouse architecture (Spark, PySpark, Delta Lake), scalable data pipeline frameworks, and constructing dependable enterprise data platforms that support operational systems, analytics platforms, and AI/ML workloads, with a strong emphasis on data governance, quality, and stewardship.