NVIDIASenior Staff Software Engineer - Data Engineering
NVIDIA is hiring a Senior Staff Software Engineer - Data Engineering in Santa Clara, United States. It pays $200k-$322k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this data engineer role is Little AI ●○○○: aI is not part of the work.
- The listed pay starts 33% above the typical data engineer posting on Level.
- Tools and skills the posting cites include Databricks, Python and SQL.
- Level lists 2,700+ other open roles at NVIDIA.
- The role was posted within the past week.
AI in this role
Build and operate data engineering pipelines and models for cloud cost allocation, forecasting, and optimization in the FinOps team.
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 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 October 27, 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.How we rate this
Senior Staff Software Engineer - Data Engineering at NVIDIA rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $200k
- Typical data engineer job
- $150k
This posting starts 33% above the typical data engineer job. See data engineer jobs
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where pipelines was part of your work. What did you do?
- Tell me about a project where finops was part of your work. What did you do?
- Tell me about a project where cost optimization was part of your work. What did you do?
- Tell me about a project where data modeling was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Engineering, Pipelines, Finops, Cost Optimization, and Data Modeling. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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