Supply Chain Data Engineer
Apache Airflow
Automation
Big Data
Bigquery
Cloud
Cloud Platform
Data
Data Architecture
Data Build Tool
Data Engineer
Data Engineering
Data Governance
Data Integration
Data Management
Data Modeling
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Warehouse
Data Warehousing
Database
Databases
ETL
Information Technology (IT)
Snowflake
SQL
Supply Chain
Job Description
Join NVIDIA in Santa Clara as a hands-on Supply Chain Data Engineer. This onsite role offers a competitive compensation range of USD 152,000 – 287,500 per year plus equity, and the opportunity to shape planning decisions at the intersection of forecasting and procurement. You will report to executive leadership and collaborate with modeling, procurement, operations, and IT teams to turn data into strategic action. Expect a role that values practical data engineering, strong data governance, and cross-functional partnership in a fast-paced, high-impact environment.
Benefits
- Equity
Responsibilities
- Design, implement, and scale automated data pipelines using SQL and Python to extract, transform, and load large supply chain datasets from internal and external systems.
- Guard data quality as the primary custodian by building automated validation scripts to catch anomalies, missing inputs, and historical mismatches before data enters planning frameworks.
- Develop and improve automated pipelines feeding downstream machine learning and AI models, ensuring data is clean, low-latency, and ready for advanced computation.
- Architect and maintain highly optimized data tables, views, and schemas tailored for rapid querying by unified computational systems.
- Collaborate to deconstruct legacy, decentralized planning workflows and migrate them to automated, centralized data environments that link forecasting to procurement.
- Work cross-functionally with engineering, global procurement, operations, and IT to uncover 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 with mastery of SQL and Python, including data manipulation with Pandas.
- 7+ years of data pipeline experience, with a proven track record of building and operating automated ETL/ELT pipelines in production.
- Deep experience with relational databases, data warehouses (Snowflake, BigQuery), or large ERP systems (SAP or Oracle).
- Extreme attention to detail and a strong focus on data integrity; you proactively identify and fix issues in large datasets.
- High autonomy and comfort starting from loose guidelines to deliver robust, production-ready data pipelines from scratch.
Technologies
- SQL
- Python
- Pandas
- Snowflake
- BigQuery
- SAP
- Oracle
- Apache Airflow
- dbt
- AWS
- Azure
- GCP
- MATLAB
Ways to stand out from the crowd
- 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 such as MATLAB or advanced Python packages.
- Familiarity with workflow orchestration tools like Apache Airflow or dbt, or infrastructure used to support Machine Learning pipelines (DataOps).
- Experience cloud-architecting supply chain master data on AWS, Azure, or GCP.
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