1 day ago
Base Salary
$168k - $322k/yr
Responsibilities
- Lead data strategy planning with team members and IT based on data sources, data locations, and use cases.
- Build, scale, and optimize self-service ETL frameworks and streaming pipelines for storage and real-time analytics.
- Design and implement data extraction, validation, transformation, and storage framework modules for data lakes.
- Enable self-service machine learning platforms for business units.
- Own data platform and transformation tools used in AI and ML.
- Architect, design, develop, and maintain data warehouses and data lakes for complex data ecosystems.
- Define and lead projects, collect requirements, set timelines, and deliver results.
Requirements
- Bachelor’s or Master’s degree in Computer Science or Information Systems, or equivalent experience with programming knowledge.
- 7+ years of relevant experience.
- Strong Python experience focused on data extraction and transformation.
- In-depth experience crafting ETL pipelines using Spark, SQL, and AWS/cloud technologies.
- Experience architecting, designing, developing, and maintaining data warehouses and data lakes.
- Understanding of operational processes involving semiconductor chips, boards, systems, and servers.
- Preferred experience with AWS, Kubernetes, Docker, Terraform, Parquet, Protobuf, schema evolution, semi-structured log parsing, SAP systems integration, Datamart, Business Objects, Tableau, Power BI, and Jupyter Notebooks.
- Ability to define and lead projects, gather requirements, establish timelines, and deliver results.
Benefits
- Competitive salary and generous benefits package.
- Eligible for equity and benefits.
- Base salary varies by location, experience, and comparable employee compensation.
- Applications accepted at least until September 14, 2026.
Tech Stack
Categories
Data Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.