AI Data Engineer Jobs at NVIDIA with Visa Sponsorship
AI Data Engineer roles at NVIDIA sit at the intersection of large-scale data infrastructure and applied machine learning, supporting teams building some of the most compute-intensive systems in the industry. NVIDIA has a consistent track record of sponsoring work visas for this function, covering H-1B, E-3, and permanent residence pathways.
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INTRODUCTION
We are looking for a Manager of Data & AI Engineering who combines deep technical expertise with strong delivery leadership and people management. This role will drive the build-out of our next-generation autonomous data intelligence platform for Supply Chain Operations — from identifying high-impact opportunities to architecting, building, and productionizing solutions that deliver measurable business value. The ideal candidate brings hands-on experience in architecture and engineering while demonstrating the ability to manage a high-performing team. This person will partner with business collaborators, translate operational challenges into data and AI solutions, and deliver at pace.
ROLE AND RESPONSIBILITIES
- Design and build scalable data and AI platforms using Databricks, AWS, and modern cloud-native engineering patterns.
- Deliver robust ETL/ELT, streaming, and CDC pipelines using technologies such as Spark, Kafka, Delta Lake, and AWS-native services.
- Enable delivery of AI-powered use cases including RAG applications, AI agents, tool-calling workflows, and data-driven web apps.
- Design data models using Star Schema, Snowflake Schema, and Data Vault patterns appropriate to the use case — optimizing for analytical query performance, data governance, and extensibility.
- Implement data quality frameworks, observability, alerting, and monitoring to ensure pipeline integrity and production reliability.
- Build the data foundation for GenAI, agentic AI, and advanced analytics initiatives, including RAG pipelines, vector search, knowledge graphs, and multi-agent orchestration patterns.
- Partner with product, business, analytics, and AI collaborators to translate requirements into secure, scalable, and production-ready solutions.
- Oversee resource planning, prioritization, project execution, and delivery across multiple concurrent initiatives, and mentor engineers, grow technical capability across the team, and develop a culture of accountability, innovation, and continuous improvement.
- Provide hands-on technical leadership across architecture, design reviews, implementation guidance, and production readiness, and handle the full lifecycle of data engineering projects — from discovery and planning through execution and production rollout.
BASIC QUALIFICATIONS
- Master's or Bachelor's degree in Computer Science or Information Systems, or equivalent experience.
- 10+ overall years in Data Engineering, Software Engineering, or web application development, with at least 3+ years specifically in a leadership or engineering management role.
- Willingness to Code: You are still a builder at heart. You are excited to spend your time writing code, prototyping, and building production systems alongside your team.
- AWS Proficiency: Intimate knowledge of the AWS ecosystem, including Amazon S3, EC2, IAM, Lambda, and API Gateway.
- Agentic AI & LLM Mastery: Proven experience operationalizing Large Language Models (LLMs) into autonomous agents that can plan, use tools, and implement multi-step workflows.
- Databricks Mastery: Proven deep expertise in Apache Spark, PySpark, Delta Lake, and Databricks Workflows. Hands-on experience scaling Unity Catalog is highly preferred.
PREFERRED QUALIFICATIONS
- Active Databricks Certifications (e.g., Data Engineer Professional, Generative AI Engineer Associate).
- Active AWS Certifications (e.g., Certified Data Engineer – Associate or Solutions Architect – Professional).
- Background in managing multi-functional teams that blend data engineers with front-end and back-end software developers.
- Knowledge of supply chain business processes for Plan, Make, Deliver & Services.
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 26, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.

INTRODUCTION
We are looking for a Manager of Data & AI Engineering who combines deep technical expertise with strong delivery leadership and people management. This role will drive the build-out of our next-generation autonomous data intelligence platform for Supply Chain Operations — from identifying high-impact opportunities to architecting, building, and productionizing solutions that deliver measurable business value. The ideal candidate brings hands-on experience in architecture and engineering while demonstrating the ability to manage a high-performing team. This person will partner with business collaborators, translate operational challenges into data and AI solutions, and deliver at pace.
ROLE AND RESPONSIBILITIES
- Design and build scalable data and AI platforms using Databricks, AWS, and modern cloud-native engineering patterns.
- Deliver robust ETL/ELT, streaming, and CDC pipelines using technologies such as Spark, Kafka, Delta Lake, and AWS-native services.
- Enable delivery of AI-powered use cases including RAG applications, AI agents, tool-calling workflows, and data-driven web apps.
- Design data models using Star Schema, Snowflake Schema, and Data Vault patterns appropriate to the use case — optimizing for analytical query performance, data governance, and extensibility.
- Implement data quality frameworks, observability, alerting, and monitoring to ensure pipeline integrity and production reliability.
- Build the data foundation for GenAI, agentic AI, and advanced analytics initiatives, including RAG pipelines, vector search, knowledge graphs, and multi-agent orchestration patterns.
- Partner with product, business, analytics, and AI collaborators to translate requirements into secure, scalable, and production-ready solutions.
- Oversee resource planning, prioritization, project execution, and delivery across multiple concurrent initiatives, and mentor engineers, grow technical capability across the team, and develop a culture of accountability, innovation, and continuous improvement.
- Provide hands-on technical leadership across architecture, design reviews, implementation guidance, and production readiness, and handle the full lifecycle of data engineering projects — from discovery and planning through execution and production rollout.
BASIC QUALIFICATIONS
- Master's or Bachelor's degree in Computer Science or Information Systems, or equivalent experience.
- 10+ overall years in Data Engineering, Software Engineering, or web application development, with at least 3+ years specifically in a leadership or engineering management role.
- Willingness to Code: You are still a builder at heart. You are excited to spend your time writing code, prototyping, and building production systems alongside your team.
- AWS Proficiency: Intimate knowledge of the AWS ecosystem, including Amazon S3, EC2, IAM, Lambda, and API Gateway.
- Agentic AI & LLM Mastery: Proven experience operationalizing Large Language Models (LLMs) into autonomous agents that can plan, use tools, and implement multi-step workflows.
- Databricks Mastery: Proven deep expertise in Apache Spark, PySpark, Delta Lake, and Databricks Workflows. Hands-on experience scaling Unity Catalog is highly preferred.
PREFERRED QUALIFICATIONS
- Active Databricks Certifications (e.g., Data Engineer Professional, Generative AI Engineer Associate).
- Active AWS Certifications (e.g., Certified Data Engineer – Associate or Solutions Architect – Professional).
- Background in managing multi-functional teams that blend data engineers with front-end and back-end software developers.
- Knowledge of supply chain business processes for Plan, Make, Deliver & Services.
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 26, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
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Get Access To All JobsTips for Finding AI Data Engineer Jobs at NVIDIA Jobs
Align your portfolio with NVIDIA's data stack
NVIDIA's AI Data Engineer roles consistently prioritize hands-on experience with GPU-accelerated data pipelines, RAPIDS, and large-scale feature engineering. Build and document projects using these tools before applying so your work speaks directly to their technical bar.
Target teams that file E-3 petitions directly
NVIDIA processes E-3 petitions in-house rather than routing through a staffing firm, which matters for Australians. Your offer letter and Labor Condition Application come from NVIDIA itself, giving you a cleaner record for future renewals and green card sponsorship.
Flag your visa type early in recruiter conversations
NVIDIA recruiters handle high application volumes for AI Data Engineer roles. Disclosing your H-1B or E-3 requirement before the technical screen lets the recruiting coordinator loop in immigration counsel early and avoids delays after an offer is extended.
Understand how NVIDIA structures PERM for this role
EB-2 and EB-3 PERM filings for AI Data Engineers at NVIDIA typically require demonstrating that the role demands a specific technical degree, not just any bachelor's. Review how DOL defines minimum requirements for your job title before your offer negotiation.
Use Migrate Mate to surface open AI Data Engineer roles at NVIDIA
Roles at NVIDIA that carry active visa sponsorship don't always stay open long. Browse AI Data Engineer listings at NVIDIA on Migrate Mate, which filters specifically for sponsored positions so you're not wasting applications on roles that won't support your visa category.
Prepare your credential documentation before the offer stage
NVIDIA's immigration team will need certified transcripts and, for candidates with three-year degrees, a credential evaluation confirming U.S. equivalency. Commission that evaluation through a NACES-member service before you receive an offer so you're not holding up the I-129 filing.
AI Data Engineer at NVIDIA jobs are hiring across the US. Find yours.
Find AI Data Engineer at NVIDIA JobsFrequently Asked Questions
Does NVIDIA sponsor H-1B visas for AI Data Engineers?
Yes, NVIDIA sponsors H-1B visas for AI Data Engineer roles. NVIDIA participates in the annual H-1B cap lottery each spring, and candidates with a qualifying offer can be registered. If you're already in H-1B status with another employer, NVIDIA can also file an H-1B transfer, letting you start without waiting for a new cap cycle.
Which visa types does NVIDIA commonly use for AI Data Engineer roles?
NVIDIA sponsors H-1B and E-3 visas for AI Data Engineers at the nonimmigrant level, with E-3 available exclusively to Australian citizens. For permanent residence, NVIDIA files EB-2 and EB-3 petitions through the PERM labor certification process. The pathway offered generally depends on your nationality, current status, and how long you've been with the company.
What qualifications does NVIDIA expect for AI Data Engineer roles?
NVIDIA's AI Data Engineer roles typically require a bachelor's or master's degree in computer science, electrical engineering, or a closely related technical field. Practical experience with distributed data systems, ML pipelines, and GPU computing frameworks matters as much as credentials. Candidates who can demonstrate production-scale work, rather than academic projects only, tend to advance further in the technical interview process.
How do I apply for AI Data Engineer jobs at NVIDIA?
You can browse open AI Data Engineer positions at NVIDIA through Migrate Mate, which surfaces roles that include visa sponsorship. Once you identify a role, apply directly through NVIDIA's careers portal. Tailor your resume to reflect the specific data infrastructure and ML tooling called out in the job description, and be prepared for multiple technical rounds assessing systems design and applied machine learning.
How do I understand the timeline from offer to work authorization at NVIDIA?
For H-1B transfers or cap-exempt filings, USCIS standard processing runs three to six months, though NVIDIA commonly uses premium processing to compress that to 15 business days. E-3 applicants pursuing consular processing in Australia can often complete the visa interview within a few weeks of the Labor Condition Application being certified by DOL. Starting the immigration process immediately after signing your offer avoids unnecessary gaps in authorization.
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