Customer Success Insights Engineer

Details

NVIDIA's Customer Success Business Insights team is looking for an engineer to scale platform adoption through data and AI-native analytical solutions. The role focuses on surfacing how customers, partners, and developers adopt NVIDIA platforms and identifying opportunities to accelerate their success.

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.
• Use AI agents throughout the engineering lifecycle, including multi-agent build workflows, automated verification, and adversarial review gates before production or executive delivery.
• Turn ambiguous adoption questions from leadership into measurable definitions, transparent metrics, and self-service dashboards, including appropriate caveats about how signals should be interpreted.
• Develop and maintain executive dashboards and recurring analytical products tracking platform adoption, developer engagement, and ecosystem health across NVIDIA software.
• Partner with Product, Marketing, Sales Operations, and external platform vendors to source telemetry, validate data contracts, and establish measurement baselines.
• Operationalize measurement for emerging channels such as AI agent marketplaces, developer registries, and model hubs where APIs change frequently and historical data may be lost.
• Champion data quality and transparency by ensuring metrics are defensible, sources are documented, and anomalies are investigated.

Requirements

• Bachelor's degree in Computing Science, Engineering, Mathematics, or equivalent experience.
• 8+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or similar roles building production data products.
• Proven experience operationalizing large language models into autonomous agents that can plan, use tools, and implement multi-step workflows, including agent-assisted development, automated verification and review gates, or agentic pipelines shipped to production.
• Deep expertise in Apache Spark, PySpark, Delta Lake, and Databricks Workflows. Hands-on experience scaling Unity Catalog is highly preferred.
• Expert SQL and Python skills, including API-based data ingestion from enterprise systems and third-party platforms.
• Experience integrating CRM and enterprise data, such as Salesforce, with product telemetry into unified analytical models.
• Track record of building executive-facing dashboards and analytical narratives that leaders trust and act on.
• Excellent communication, stakeholder management, analytical, and problem-solving skills.

Preferred Qualifications

• Experience with NVIDIA AI technologies and platforms or measurement of developer ecosystems, including GitHub or GitLab telemetry, package registries, model hubs, and marketplace analytics.
• Experience designing multi-agent or agentic engineering workflows using Claude Code, Codex, Cursor, Nemotron, or similar tools with verification and code review gates.
• Active Databricks certifications, such as Data Engineer Professional or Generative AI Engineer Associate.
• Master's degree in Computer Science, Data Science, or equivalent experience.

Benefits

• Equity and benefits are provided.
• NVIDIA is an equal opportunity employer.

Applications will be accepted at least until August 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.