NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology—and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are seeking a highly motivated and experienced Senior Business Solutions Architect – SAP MDG with a focus on SAP MDG technical framework for Material and Business Partner domains, ensuring a "single version of truth" across the global semiconductor landscape. This role is a crucial part of our mission to transform computing, driving the design, governance, and evolution of enterprise data platforms and global business processes. As an expert in SAP MDG and data governance, you will collaborate with business stakeholders and IT teams, to deliver scalable, resilient, and forward-looking SAP MDG solutions. Your expertise will help address complex supply chain challenges, strengthen data governance and observability, and enable trusted, high-quality data across the supply chain.
What You’ll Be Doing:
Solution Architecture: Architect and implement end-to-end SAP MDG solutions for Material (MDG-M), Business Partner (MDG-S/C), and BOM, ensuring seamless master and reference data management across the global supply chain.
Data Orchestration: Design and configure complex data integration pipelines using the Data Replication Framework (DRF), SOA Manager, and OData, supporting real-time and batch synchronization between S/4HANA, SFDC, PLM, and Informatica.
Governance Framework: Lead the deployment of enterprise governance capabilities, including Custom Data Models, Rule-Based Workflows (BRF+), and stewardship frameworks to automate data catalogs and lineage tracking.
Data Quality & Observability: Establish a proactive data observability layer using SAP DQM and Power BI/ Tableau to monitor data health, validation accuracy, and operational KPIs across all manufacturing domains.
Support & Enhancement: Provide expert production support for SAP MDG to ensure 24/7 data availability and seamless synchronization. Also, focusing on the continuous enhancement to resolve complex technical issues and optimize performance for all data domains.
Collaborate with different IT teams and business to translate complex supply chain and semiconductor requirements into scalable, governed, and business-aligned data solutions.
What we need to see:
8+ years of SAP MDG experience with two end-to-end Greenfield implementations across Material (MDG-M) and Business Partner (MDG-S/C). Experience specifically within the Semiconductor industry is preferred.
Governance Framework: Expert knowledge of Change Request (CR) management, including status management, header/item relationships, and Consolidation & Mass Processing for large-scale data updates.
Data Modelling: Advanced experience in Data Modeling enhancements and the creation of Custom Data Models to meet specialized semiconductor business requirements.
Proficiency in Fiori/UI customization, including Floor Plan Manager (FPM) and Web Dynpro, to optimize the requester, and approver experience.
Data Quality & Rules: Advanced use of SAP DQM for validation/derivation and BRF+ for complex rule-based workflows.
Integration & Replication: Expert-level configuration of the Data Replication Framework (DRF), including filter criteria, manual replication, and end-to-end testing across IDoc (ALE/EDI), SOA (Web Services), OData, and XML.
Landscape Interfacing: Proven experience synchronizing master data between SAP S/4HANA, SFDC, PLM, and Informatica.
Deep understanding of supply chain and manufacturing data domains, including Material Master, BOM, Product Data, Supplier Data, and Reference Data across cross-functional processes.
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.
Familiarity with AI-enabled productivity and data platforms such as ChatGPT, Copilot, Gemini, or Claude to improve automation, data quality, and decision-making.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, results-oriented and enjoy having fun, then what are you waiting for? Apply today!
