Senior Data Engineer at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Operations, ManufacturingIndustries

Requirements

Master’s or Bachelor’s degree in Computer Science or Information System, or equivalent experience
8+ years of relevant experience including programming knowledge (i.e., SQL, Python, Java, etc.)
Highly independent, able to lead key technical decisions, influence project roadmap, and work effectively with team members
Experience architecting, designing, developing, and maintaining data warehouses/data lakes for complex data ecosystems
Expert in data and database management including data pipeline responsibilities in replication and mass ingestion, streaming, API and application and data integration
Experience in developing required infrastructure for optimal extraction, transformation, and loading of data from various sources using Databricks, AWS, Azure, SQL or other technologies
Strong analytical skills with the ability to collect, organize, and disseminate significant amounts of information with attention to detail and accuracy
Knowledge in operational processes in chips, boards, systems, and servers with a view of data landscape
Knowledge of supply chain business processes for planning, procurement, shipping, and returns

Responsibilities

Develop and implement the new End-to-End Data systems for Planning, Logistics and Services, and Sourcing initiatives
Lead discussions with stakeholders and IT to identify and implement the right data strategy given data sources, data locations, and use cases
Build data pipelines to transport data from a data source to the data lake
Analyze and organize raw operational data including structured and unstructured data
Build data systems and pipelines ensuring that data sources, ingestion components, transformation functions, and destination are well understood for implementation
Interpret trends and patterns by performing complex data analysis
Prepare data for prescriptive and predictive modeling by making sure that the data is complete, has been cleansed, and has the necessary rules in place
Build/develop algorithms, prototypes, and analytical tools that enable the Ops teams to make critical business decisions
Build data and analytic solutions for key initiatives to set up manufacturing plants in US
Support key strategic initiatives like building scalable cross-functional datalake solutions

Skills

SQL

Python

Java

Data Pipelines

Data Lake

Data Warehousing

ETL

Data Analysis

Algorithms

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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