Supply Chain Data Engineer

NVIDIA•Santa Clara, CA

3d•$152,000 - $287,500

About The Position

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. You will 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. Are you excited about this mission? If you are an absolute data purist who loves building bulletproof pipelines and wants to see your infrastructure directly drive unified planning decisions from data to execution, this is your role!

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Industrial Engineering, Operations Research, or equivalent experience.
Mastery in SQL and Python (specifically data manipulation libraries like Pandas) is non-negotiable.
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, BigQuery), or large enterprise ERP systems (like SAP or Oracle).
A hyper-focused mindset regarding data integrity; you are someone who finds a missing cell or a formatting glitch in a million-row dataset satisfying to solve.
Comfortable operating with loose initial guidelines to build robust, production-ready data pipelines from scratch.

Nice To Haves

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)

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. 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. Make sure 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.