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. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world!
We are looking for a Senior Staff Software Engineer focused on data engineering to join NVIDIA’s FinOps team. You will build and operate the pipelines and data models behind cost allocation, forecasting and optimization. Your work will make data more reliable and help the team onboard new sources without repeated manual effort.
What you will be doing:
- Design, build and operate production pipelines using Python, SQL and Databricks/Spark for cloud billing, SaaS usage and shared-service telemetry.
- Build reusable ingestion frameworks and data contracts for APIs and file-based sources, handling schema changes, late-arriving data and safe backfills.
- Develop cost, usage and ownership models for BU, platform and service allocation, with reconciliation and traceability to source records.
- Implement data freshness, completeness and accuracy checks, lineage and actionable monitoring. Diagnose incidents and automate retries, replay and recovery.
- Optimize distributed processing, storage and serving-layer queries for performance, scalability and infrastructure cost.
- Own testing, CI/CD, safe deployments and operational runbooks for data services, and participate in production support.
- Partner with Finance, infrastructure and service owners to turn reporting and governance requirements into clear data models and interfaces.
- Lead technical design and code reviews, mentor engineers, and apply access controls and auditability throughout the data lifecycle.
What we need to see:
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering or a related field, or equivalent experience.
- 12+ years of software or data engineering experience building and operating production data systems.
- Strong Python and SQL skills, with experience writing maintainable, tested code and debugging complex data transformations.
- Hands-on experience with Databricks, Apache Spark and lakehouse technologies, or comparable distributed data platforms.
- Experience with data modeling, incremental processing, partitioning, schema evolution and analytical query performance.
- Experience building cloud-based pipelines and integrating REST APIs, including authentication, pagination, rate limits and error handling.
- A track record of owning production reliability through automated tests, data quality checks, monitoring, incident diagnosis and recovery.
- Clear technical communication and the ability to resolve ambiguous data requirements with engineering and business partners.
- Experience with Git, CI/CD and secure handling of credentials and data access. Sound judgment when using AI coding tools and validating generated code.
Ways to stand out from the crowd:
- Familiarity with FinOps, cloud billing datasets, FOCUS, SaaS license utilization or cost-allocation models across cloud and shared services.
- Experience with data catalogs, workflow orchestration, observability platforms or AI-assisted anomaly detection and root-cause analysis.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most intelligent and hardworking people in the world 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 other objective job-related factors. The expected base salary range for this position is 200,000 USD – 322,000 USD.You will also be eligible for equity and benefits.
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.Skills Required
- Bachelor's or Master's degree in Computer Science, Computer Engineering, a related field, or equivalent experience
- 12+ years of software or data engineering experience building and operating production data systems
- Strong Python and SQL skills, including maintainable tested code and debugging complex data transformations
- Hands-on experience with Databricks, Apache Spark, and lakehouse technologies or comparable distributed data platforms
- Experience with data modeling, incremental processing, partitioning, schema evolution, and analytical query performance
- Experience building cloud-based pipelines and integrating REST APIs, including authentication, pagination, rate limits, and error handling
- Experience owning production reliability through automated tests, data quality checks, monitoring, incident diagnosis, and recovery
- Clear technical communication and ability to resolve ambiguous data requirements with engineering and business partners
- Experience with Git, CI/CD, and secure handling of credentials and data access
- Sound judgment when using AI coding tools and validating generated code
- Familiarity with FinOps, cloud billing datasets, FOCUS, SaaS license utilization, or cost-allocation models
- Experience with data catalogs, workflow orchestration, observability platforms, or AI-assisted anomaly detection and root-cause analysis
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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