Are you passionate about bridging the gap between manufacturing operations and data analytics? At NVIDIA, we’re on the lookout for an ambitious and dedicated Data Systems Analyst to join our SCBT Operations Data Platform DataOps organization in Hsinchu City, Taiwan. As part of a world-class team, you'll drive operational excellence and ensure detailed data integrity across our manufacturing processes. This is your chance to create a significant impact on our supply chain performance and contribute to NVIDIA’s groundbreaking innovations!

What you'll be doing:

• Drive business insights to enhance manufacturing efficiency, operational execution, and supply chain performance.

• Enable and monitor shop-floor data collection for new and existing contract manufacturers and suppliers.

• Identify gaps in operational processes and recommend improvements to ensure seamless manufacturing operations.

• Establish and maintain data quality attributes and metrics, ensuring data integrity across manufacturing operations.

• Audit manufacturing data quality, address anomalies, and implement validation processes for greater accuracy and visibility.

• Collaborate with external partners and internal engineering teams to resolve production data discrepancies and support product implementation requirements.

• Manage production configuration information, maintaining integrity of manufacturing attributes, component relationships, and product structures.

• Partner with IT, planning, and engineering teams to translate operational requirements into scalable solutions and support continuous improvement initiatives.

What we need to see:

• Bachelor’s or Master’s degree in Industrial Engineering, Supply Chain Management, Information Systems, Computer Science, or equivalent practical experience.

• 5+ years of experience in electronics manufacturing operations, outsourced manufacturing, supply chain, or related fields.

• Strong knowledge of hardware manufacturing processes, product assembly flows, and outsourced manufacturing operations.

• Experience with Shop Floor Control Systems (SFCS), Shop Floor Control Systems (SFCS), Manufacturing Execution Systems (MES), Engineering Change Order (ECO) processes, Product Lifecycle Management(PLM), product configuration management, and BOM structures.

• Basic to intermediate SQL skills for manufacturing data queries, validation, troubleshooting, and analysis.

• Ability to leverage AI-assisted tools and modern technologies to improve operational efficiency and support data-driven decisions.

• Strong analytical, problem-solving, communication, and cross-functional collaboration skills.

• Self-motivated and detail-oriented, with sound judgment and the ability to work independently in a fast-paced environment, to collaborate effectively with engineering teams, business collaborators, and external manufacturing partners.

Ways to stand out from the crowd:

• Experience with manufacturing operations and supply chain management.

• Knowledge of manufacturing operational processes covering components, boards, systems, and server products.

• Proficiency in writing and optimizing complex SQL queries for manufacturing analytics and operational reporting.

• Experience with scripting or programming languages such as Python or Java for automation and data processing, crafting dashboards and reports using Tableau, Power BI, or similar visualization platforms.

• Familiarity with systems administration, virtual machines, cloud platforms (AWS, Azure), and data pipeline concepts.

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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