Nvidia
Customer Success Insights Engineer
US, CA, Santa Clara · Senior
Sponsorship not specifiedDetected 2 days ago
PythonCode ReviewGitSQLDatabricksSparkData EngineeringData ScienceLLMsAgentic AIStakeholder ManagementSalesforceCRMSalesCustomer SuccessUnityLeadershipCommunicationProblem Solving
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odds of building a lasting career here
42Risky
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
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Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Context, not a finding about this posting: of this employer's 843 green-card filings in this occupation, 97% were for a worker who already held the job.
Green-card follow-through: 95%
Of 584 labor certifications old enough to have been used, 29 expired without the employer filing the next step. Median time from filing to decision: 497 days.97% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.
Files H-1B transfers
620 transfer filings in the last year, covering 1241 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
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About the role
- NVIDIA is widely considered to be one of the technology world's most desirable employers.
- We have some of the most forward-thinking and hardworking people in the world working for us!
- Turn ambiguous adoption questions from leadership into measurable definitions, transparent metrics, and self-serve dashboards, including the caveats: knowing when signals must not be summed, funneled, or over-claimed.
Responsibilities
- Design, build, and operate automated data collection and transformation pipelines across enterprise systems, vendor APIs, and public developer platforms into Databricks, with data quality gates, freshness monitoring, and fail-safe behavior built in from day one.
- Use AI agents throughout the engineering lifecycle: multi-agent build workflows, automated verification, and adversarial review gates before anything reaches production or an executive audience.
- Partner with Product, Marketing, Sales Operations, and external platform vendors to source new telemetry, validate data contracts, and establish baselines before changes ship, so every initiative gets a measured before and after.
- Agentic AI & LLM Mastery: Proven experience operationalizing Large Language Models (LLMs) into autonomous agents that can plan, use tools, and implement multi-step workflows, applied to real engineering: agent-assisted development, automated verification and review gates, or agentic pipelines that shipped to production.
- A track record of building executive-facing dashboards and analytical narratives that leaders trust and act on.
- You'll surface how customers, partners, and developers adopt NVIDIA platforms - and where we can accelerate their success.
- multi-agent build workflows, automated verification, and adversarial review gates before anything reaches production or an executive audience.
Requirements
- What we need to see: BS degree in Computing Science, Engineering, Math or equivalent experience.
- 8+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or similar roles in building production data products.
- BS degree in Computing Science, Engineering, Math or equivalent experience.
Nice to have
- Hands-on experience scaling Unity Catalog is highly preferred.
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 168,000 USD - 258,750 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5.
Benefits
- Develop and maintain executive dashboards and recurring analytical products that track platform adoption, developer engagement, and ecosystem health across NVIDIA software.
Company info
- Ways to stand out from the crowd: Background with NVIDIA AI technologies and platforms, or measurement of developer ecosystems (GitHub/GitLab telemetry, package registries, model hubs, marketplace analytics).
Equal opportunity
- NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer.
This listing is sourced directly from Nvidia's careers page and normalized into a canonical job model.