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
At NVIDIA, you will join a collaborative environment that emphasizes data-driven decisions and cross-functional partnership. This onsite role in Santa Clara offers the chance to own production-grade data pipelines, curate large datasets for forecasting and procurement, and influence unified planning decisions at the executive level. You will partner with modeling, procurement, operations, and IT teams, reporting to leadership. The compensation range for this role is USD 152,000 to 287,500 per year, with equity included as part of the benefits package.
Responsibilities
- Design, implement, and scale automated data pipelines using SQL and Python to extract, transform, and load large supply chain datasets from both internal and external systems.
- Data quality stewardship: develop automated validation scripts to detect anomalies, missing inputs, and historical inconsistencies before data enters planning frameworks.
- Enhance pipelines that feed downstream machine learning and AI models, ensuring data is clean, low-latency, and prepared for advanced computation.
- Infrastructure management: create and maintain optimized data tables, views, and schemas tailored for rapid querying by unified computational systems.
- Systems deconstruction: collaborate to migrate legacy, decentralized planning workflows into automated, centralized data environments that link forecasting to procurement.
- Cross-functional collaboration: work closely with engineering, global procurement, operations, and IT teams 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 in SQL and Python, including data manipulation with Pandas.
- 7+ years of data pipeline experience, with a proven track record of building and running automated ETL/ELT pipelines in production.
- Deep experience with relational databases, data warehouses (eg Snowflake, BigQuery), or large ERP systems (such as SAP or Oracle).
- Extreme attention to detail and a strong focus on data integrity; thrives on resolving missing values and formatting issues in large datasets.
- High autonomy and comfort working with flexible guidelines to craft robust, production-ready data pipelines from the ground up.
Technologies
- SQL
- Python
- Pandas
- Snowflake
- BigQuery
- SAP
- Oracle
- Apache Airflow
- dbt
- AWS
- Azure
- GCP
- MATLAB
Benefits
- Equity
Ways to stand out from the crowd
- Experience building data infrastructure within semiconductor, electronics, or large-scale technology hardware supply chains.
- Background with mathematical modeling environments, advanced computation engines, or algorithmic simulation software (eg MATLAB, advanced Python packages).
- Familiarity with workflow orchestration tools (such as Apache Airflow or dbt) or infrastructure used to support Machine Learning pipelines (DataOps).
- Experience cloud-architecting supply chain master data across AWS, Azure, or GCP.
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