Supply Chain Data Engineer

NVIDIA is seeking a high-caliber, hands-on data engineer specializing in supply chain to act as the ultimate data custodian.

Your mission is to replace manual workflows with automated, production-grade data pipelines.

Responsibilities:

• Personally compose, write, and scale automated data pipelines using SQL and Python to extract, transform, and load large supply chain datasets from internal and external systems.
• Serve as the primary guardian of data quality, building automated validation scripts to catch anomalies, missing inputs, and historical mismatches.
• Build and improve automated pipelines that feed downstream machine learning and AI models.
• Architect and maintain highly optimized data tables, views, and schemas specifically structured for rapid querying by unified computational systems.
• Partner with the team to deconstruct legacy, decentralized planning workflows and systematically migrate them into automated, centralized data environments.
• Sync closely with engineering, global procurement, operations, and IT teams to unearth hidden data sources and standardize core supply chain metrics.

Requirements:

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Industrial Engineering, Operations Research, or equivalent experience.
• Expert Data Engineering Skills: Mastery in SQL and Python (specifically data manipulation libraries like Pandas).
• 7+ Years of Data Pipeline Experience: Proven track record of personally building and running automated ETL/ELT pipelines in a production setting.
• Database Expertise: Deep experience working with relational databases, data warehouses (e.g., Snowflake, BigQuery), or large enterprise ERP systems (like SAP or Oracle).
• Extreme Detail Orientation: A hyper-focused mindset regarding data integrity.
• High Autonomy: Comfortable operating with loose initial guidelines to build robust, production-ready data pipelines from scratch.

Preferred Qualifications:

• Prior experience building data infrastructure within the semiconductor, electronics, or large-scale technology hardware supply chains.
• Background with mathematical modeling environments, advanced computation engines, or algorithmic simulation software (e.g., MATLAB, advanced Python packages).
• Familiarity with workflow orchestration tools (like Apache Airflow or dbt) or basic infrastructure used to support Machine Learning pipelines (DataOps).
• Experience cloud-architecting supply chain master data (AWS, Azure, GCP).

You will also be eligible for equity and benefits.