Supply Chain Data Engineer

Overview

NVIDIA is seeking a high-caliber, hands‑on data engineer specializing in supply chain to act as the ultimate data custodian. This person will build the foundation for our fully coordinated forecasting and supply‑chain ecosystem. In this critical role, you will form a tight team with our Principal Modeling Engineer and report directly into executive leadership. Your mission is to replace manual workflows with automated, production‑grade data pipelines.

Personally compose, curate, and maintain the massive datasets—encompassing semiconductor wafers, memory, substrates, and critical long‑lead‑time sub‑assemblies—that feed our multi‑billion‑dollar simulation engines. If you are an absolute data purist who loves building bullet‑proof pipelines and wants to see your infrastructure directly drive unified planning decisions from data to execution, this is your role.

• 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: build automated validation scripts to catch anomalies, missing inputs, and historical mismatches before they enter our advanced planning frameworks.
• Build and improve automated pipelines that feed downstream machine learning and AI models, ensuring data is clean, low‑latency, and accurately prepared for advanced computation.
• Architect and maintain highly optimized data tables, views, and schemas specifically structured for rapid querying by our unified computational systems.
• Partner with the team to deconstruct legacy, decentralized planning workflows and systematically migrate them into automated, centralized data environments that tie forecasting directly to procurement.
• Sync closely with engineering, global procurement, operations, and IT teams to unearth hidden data sources and standardize core supply‑chain metrics.

• 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.
• Deep experience working with relational databases, data warehouses (e.g., Snowflake, Big Query), or large enterprise ERP systems (like SAP or Oracle).
• Extreme detail orientation: a hyper‑focused mindset regarding data integrity; excellent at spotting and correcting formatting glitches in large datasets.
• High autonomy: comfortable operating with loose initial guidelines to build robust, production‑ready data pipelines from scratch.

• 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 (Data Ops).
• Experience cloud‑architecting supply‑chain master data (AWS, Azure, GCP).

Base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $152,000‑$230,000 for Level4, and $184,000‑$287,500 for Level
5. You will also be eligible for equity and benefits.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal‑opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.