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Nvidia Data Analytics Jobs (NOW HIRING)

OR · On-site

Academic and commercial groups worldwide are using NVIDIA products to redefine deep learning, data analytics, and power data centers. Join the team building many of the world's largest and fastest ...

OR · On-site

Academic and commercial groups worldwide are using NVIDIA products to redefine deep learning, data analytics, and power data centers. Join the team building many of the world's largest and fastest ...

OR · Hybrid

NVIDIA's Developer Technology Engineering team is a global network of world-class experts pushing ... Strong background in distributed high-performance data analytics including SQL or vector databases.

OR · On-site

... NVIDIA's Data Center related products. We are a data-driven team, dedicated to identifying and resolving issues by analyzing network results, conducting engineering experiments, and performing lab ...

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Nvidia Data Analytics information

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$24

$54

$94

How much do nvidia data analytics jobs pay per hour?

As of Jun 6, 2026, the average hourly pay for nvidia data analytics in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Nvidia Data Analytics professional, and why are they important?

To excel as an Nvidia Data Analytics professional, you need strong analytical skills, expertise in statistics, and a solid background in computer science or data science, often supported by relevant degrees or certifications. Proficiency with Nvidia’s GPU computing platforms (such as CUDA), data analytics tools (like Python, R, and SQL), and experience with machine learning frameworks are typically required. Excellent problem-solving abilities, communication skills, and a collaborative mindset help you interpret data insights and work effectively within multidisciplinary teams. These abilities are crucial for leveraging advanced analytics to drive innovation and informed decision-making at Nvidia.

What is the difference between Nvidia Data Analytics vs Data Scientist?

AspectNvidia Data AnalyticsData Scientist
Required CredentialsBachelor's in Computer Science, Data Analytics, or related fields; knowledge of Nvidia toolsBachelor's or higher in Computer Science, Statistics, or related fields; often advanced degrees
Work EnvironmentTech companies, data centers, AI labs using Nvidia hardware and softwareVarious industries including tech, finance, healthcare; research and development roles
Employer & Industry UsagePrimarily in AI, machine learning, and data processing with Nvidia platformsAcross industries for data analysis, modeling, and insights generation

While Nvidia Data Analytics focuses on leveraging Nvidia hardware and software for data processing and AI tasks, Data Scientists perform broader data analysis, modeling, and interpretation across various tools and platforms. Both roles require strong analytical skills, but Nvidia Data Analytics is more specialized in Nvidia technologies.

What are some common challenges faced by data analytics professionals at Nvidia, and how are they typically addressed?

Data analytics professionals at Nvidia often encounter challenges such as working with large, complex datasets and ensuring data quality across diverse sources. Additionally, they must stay updated with rapidly evolving analytics tools and technologies used within the company. Collaboration is key, as analytics teams regularly partner with engineering, product, and business units to align insights with strategic goals. To address these challenges, Nvidia fosters a culture of continuous learning, provides access to advanced computing resources, and encourages cross-functional teamwork.

What is an Nvidia Data Analytics professional?

An Nvidia Data Analytics professional is someone who uses Nvidia's hardware and software solutions to analyze large datasets, often leveraging GPU acceleration for faster data processing and advanced analytics. These professionals may work with Nvidia tools like RAPIDS, CUDA, and AI frameworks to perform tasks such as data preprocessing, machine learning, or deep learning. They play a key role in optimizing data workflows, improving model performance, and helping organizations make data-driven decisions, particularly in industries requiring high computational power.
Infographic showing various Nvidia Data Analytics job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $113,873 per year, or $54.7 per hour.
Solutions Architect, Data Center Infrastructure - NVIS

Solutions Architect, Data Center Infrastructure - NVIS

Nvidia

Santa Clara, CA

Full-time

Posted 3 days ago


Job description

NVIDIA is seeking a Solutions Architect in Data Center Infrastructure to join our Infrastructure Specialists team. Academic and commercial groups worldwide are using NVIDIA products to redefine deep learning, data analytics, and power data centers. Join the team building many of the world's largest and fastest data centers and supercomputers! NVIDIA is looking for someone who can lead planning and deployments of AI data centers including power/cooling systems, cabling and network provisioning and bring-up/validation.

As the NVIS Solutions Architect for Datacenter Infrastructure, you will focus on data center audit, planning and deployment ensuring the integrity of NVIDIA platform infrastructure. Your primary goal will be to guarantee that all aspects of the data center's physical infrastructure are meticulously planned, implemented, and validated to meet NVIDIA reference architectures, operational requirements, and industry standards. This infrastructure includes architectural systems, power distribution, liquid/air cooling systems, compute, network and cabling (fiber and copper), and telemetry systems.

What you will be doing:

  • NVIS Datacenter Engineering and planning: Collaborate with other teams to plan and implement data center infrastructure solutions based on NVIDIA Datacenter reference architecture, including power distribution, cooling systems, network architecture, server hardware, and storage systems.

  • Plan and manage deployment of NVIDIA's pioneering AI infrastructure solutions including highly complex rack-scale, liquid cooled compute and networking hardware systems, in a fluid and fast paced environment.

  • Conduct pre-deployment planning including reviewing cluster and data center architecture, plan network port mapping and fiber optic cabling BOM, identify potential risks, train vendors and find areas for improvement.

  • Evaluate customers' and partners' infrastructure design proposals for consistency with industry standards and regulatory requirements. Provide feedback and recommendations to improve performance, scalability, and cost-effectiveness.

  • Perform testing, troubleshooting and validation of compute systems based on collaboration with product and engineering teams.

  • Act as the NVIS mentor providing guidance, mentorship, and support to ensure the NVIS team's success in their respective roles.

  • Quality Assurance: Establish and enforce quality assurance processes to verify that deployments meet established specifications and performance benchmarks. Conduct thorough bring-up, testing, and validation to validate the functionality and reliability of infrastructure components.

  • Continuous Improvement: Drive continuous improvement initiatives to enhance data center infrastructure efficiency for NVIDIA data center reference architecture and deployment blueprint, resilience, and sustainability. Find opportunities to streamline processes, automate repetitive tasks, and leverage emerging technologies to optimize infrastructure operations.

  • Collaboration and Communication: Collaborate and communicate across internal teams, external vendors, and customers to facilitate the seamless integration of data center infrastructure solutions. Serve as a domain expert and point of contact for infrastructure-related inquiries and blocking issues.

What we need to see:

  • Bachelor's degree (or equivalent experience) in Engineering, Computer Science, Information Technology, or a related field.

  • Minimum 3+ years of overall experience in enterprise and/or hyperscale data centers with continual infrastructure deployment experience, preferably for high density AI/HPC data centers.

  • Working experience in data center operations, or infrastructure management roles, focusing on large-scale data center deployments.

  • Strong technical knowledge and experience in the data center stack - power distribution, liquid cooling, servers, networking, storage and pre-deployment planning

  • Relevant certification - preferred

  • Demonstrated technical and project leadership under fluid situations, ability to adapt to unknowns and change.

  • Excellent analytical, problem-solving, and decision-making skills, keen attention to detail, and a commitment to quality.

  • Excellent communication and interpersonal abilities, capable of engaging with various collaborators like customers to enable productive discussions.

  • Organization & Time Management - able to plan, schedule, and organize tasks related to the job to achieve goals within or ahead of established time frames.

  • Willingness to travel (up to 40%).

Way to stand out from the crowd:

  • Linux system administration skills

  • Strong knowledge of whole data center Infrastructure stack

  • Flexible/agile and enjoys solving challenging problems

NVIDIA is widely considered one of the world's most desirable employers in technology. We have some of the world's most forward-thinking and passionate people working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 3, and 148,000 USD - 235,750 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 7, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993