
Pioneering accelerated computing and AI
Senior Business Solutions Architect – Enterprise Data Management
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 – Enterprise Data Management with a focus on end-to-end supply chain to join our Business Applications team. 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 enterprise data management and data architectures/ platform, you will collaborate with business stakeholders and IT teams, to deliver scalable, resilient, and forward-looking data 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:
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Architect and implement enterprise Master Data Management (MDM) and Reference Data Management (RDM) solutions for Material Master, Bill of Materials (BOM), Customer, Supplier, and Reference Data across end-to-end supply chain processes.
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Design and implement data integration and pipeline architectures including real-time, batch, API-driven, and event-based pipelines supporting large-scale manufacturing and supply chain datasets.
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Lead the implementation of enterprise data governance capabilities, including business glossaries, data catalogs, lineage tracking, and stewardship frameworks aligned to cross-functional business processes.
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Establish a data observability layer to proactively monitor data quality, lineage, and operational health across data domains.
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Develop canonical data models, standardized taxonomies, and process-aligned data structures to enable consistent, reusable, and interoperable enterprise data.
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Partner with engineering, business and IT teams to translate complex supply chain and semiconductor requirements into scalable, governed, and business-aligned data solutions.
What We Need to See:
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10+ years of experience in enterprise data architecture, MDM, RDM, and scalable data platform solutions, preferably in end-to-end supply chain or semiconductor manufacturing environments.
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Hands-on expertise with Informatica Intelligent Data Management Cloud (IDMC) including MDM, CDI, CAI, CDGC, IDQ, Reference 360, Metadata Management, and Data Catalog capabilities.
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Strong experience with Databricks lakehouse architecture, including Spark, Py Spark, Delta Lake, and scalable data pipeline frameworks as well as proven ability to design scalable and resilient enterprise data platforms supporting operational systems, analytics platforms, and AI/ML workloads, with strong emphasis on data governance, quality, and stewardship.
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Deep understanding of supply chain and manufacturing data domains, including Material Master, BOM, Product Data, Supplier Data, and Reference Data across cross-functional processes.
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Experience designing enterprise data solution architectures, including ETL/ELT pipelines, API integrations, microservices, and event-driven data patterns.
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Strong expertise in data modeling, canonical data design, business glossaries, data catalogs, and lineage frameworks supporting enterprise governance initiatives.
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Experience integrating enterprise data platforms with ERP, PLM, including SAP S/4HANA, SAP MDG, SAP IBP, SFDC etc.
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Demonstrated ability to collaborate across cross-functional teams to deliver scalable, governed, and observable enterprise data solutions.
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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.
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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!
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NVIDIA 소개

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
직원 수
Santa Clara
본사 위치
$4.57T
기업 가치
리뷰
10개 리뷰
4.4
10개 리뷰
워라밸
2.8
보상
4.5
문화
4.2
커리어
4.3
경영진
3.8
78%
지인 추천률
장점
Cutting-edge technology and innovation
Excellent compensation and benefits
Great team culture and collaboration
단점
High pressure and expectations
Poor work-life balance and long hours
Fast-paced environment leading to burnout
연봉 정보
79개 데이터
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
7개 리포트
$170,275
총 연봉
기본급
$130,981
주식
-
보너스
-
$155,480
$234,166
면접 후기
후기 5개
난이도
3.0
/ 5
면접 과정
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
최근 소식
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
reddit/blind
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NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
reddit/blind
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NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
reddit/blind
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NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
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