Enterprise Data Management – Data Application Engineer (Supply Chain)

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.

Responsibilities

• 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.

Requirements

• 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.
• 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.
• In-depth understanding of supply chain and manufacturing data domains, including Material Master, BOM, Product Data, Supplier Data, and Reference Data throughout multi-functional processes.
• Ability to manage both procedural and functional elements of a data domain. Understand detailed process flows and business rules. Incorporate agentic AI into data applications and show (or develop) skills in ontology/knowledge graphs.
• Advanced skills in data modeling, canonical data construction, enterprise terminology collections, metadata catalogs, and lineage frameworks that aid enterprise governance initiatives.
• Experience integrating enterprise data platforms with ERP and PLM systems, such as SAP S/4HANA, SAP MDG, SAP IBP, SFDC, and associated tools.
• Understanding of efficiency and data platforms powered by advanced technology (e.g., ChatGPT, Copilot, Gemini, Claude).
• Practical experience crafting agentic AI workflows (LLM-based agents, RAG, orchestration) aimed at data quality, alerting, and observability.
• Hands-on knowledge of semiconductor chip supply planning, including chip family and part development, PLM input/output/yield relationships, and planning master data (BOM, Routing, Production Version) as they relate within SAP IBP and Anaplan.

Benefits

• Competitive salary: 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5
• Equity and benefits package