Senior Analytics Engineer, Finance
NVIDIA is hiring a Senior Analytics Engineer, Finance in Santa Clara, United States. It pays $144k-$230k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- The posting mentions Databricks, Tableau and Power BI among its tools and skills.
- Level classes it as a senior role.
- NVIDIA has 1,800+ other open roles on Level.
- Posted within the past week.
AI in this role
Design and build analytics solutions, data pipelines, and data applications supporting finance initiatives on Databricks.
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 an inclusive, 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 seeking a highly skilled Senior Analytics Engineer supporting finance initiatives, with strong end-to-end analytics capabilities, spanning data engineering fundamentals, semantic layer design, dashboard development in Tableau and Power BI, and application development within Databricks. The ideal candidate will bring strong Finance domain knowledge, experience improving reporting and business processes, hands-on expertise building semantic layers to develop consistent, well-governed analytical data models, and proficiency designing and deploying data applications on the Databricks Lakehouse Platform.
What you'll be doing:
- Design, build, and maintain analytics solutions across the full lifecycle from data ingestion to reporting and Databricks-hosted application delivery.
- Build and maintain data pipelines, notebooks, and end-user applications within Databricks, using Delta Live Tables, Unity Catalog, and Databricks SQL for governed, scalable data products.
- Collaborate with data engineering teams to optimize data pipelines, ensure data quality, and improve data availability.
- Design, implement, and support end-to-end system integrations between SAP S/4HANA and third-party platforms (e.g., lease administration system, space planning tool, physical security/badging systems).
- Ensure accurate, timely, and automated data flow from SAP to downstream systems (and vice versa) to eliminate manual handoffs and human intervention.
- Establish and implement data governance, validation rules, and transformation logic to ensure data consistency across systems including Unity Catalog policies within Databricks.
- Supervise and support interface health, error handling, and reconciliation processes, proactively resolving integration failures and data discrepancies.
- Partner closely with Finance and Real Estate & Site Services Group to understand business processes, reporting needs, and strategic priorities.
- Support data science and advanced analytics projects, including data exploration, feature preparation, and model evaluation within the Databricks environment.
What we need to see:
- Bachelor’s degree or equivalent experience in Information Systems, Analytics, Computer Science, Finance, Accounting, or a related field.
- 8+ years of proven ability designing, building, and supporting end-to-end BI and analytics solutions, from data ingestion and modeling to reporting and insights delivery.
- Hands-on experience with Databricks, including building notebooks, workflows, and data applications (Databricks Apps).
- Practical involvement with traditional data warehouse architectures, including centralized data warehouses and/or data marts, and a solid understanding of historical, snapshot, and incremental data processing patterns.
- Strong SQL skills and proficiency in data modeling concepts (star schema, dimensional modeling, semantic design).
- Demonstrable ability to identify inefficiencies and lead process improvement efforts.
- Ability to lead sophisticated projects, influence partners, and communicate effectively at both technical and executive levels.
Ways to stand out from the crowd:
- Background with ETL/ELT tools (e.g., dbt, Fivetran, Informatica, Data Factory, Alteryx) and project tracking in Jira.
- Experience building data governance processes, documentation standards, or data quality frameworks.
- Exposure to data science tools or methodologies (Python, R, machine learning concepts, Snowflake).
- Experience deploying production-grade applications using Databricks Apps and integrating them with enterprise BI tools or downstream consumers.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:144,000 USD – 230,000 USD for Level 4; and 184,000 USD – 287,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 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 Analytics Engineer, Finance 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
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- Tell me about a project where analytics engineering was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- Tell me about a project where semantic layer design was part of your work. What did you do?
- Tell me about a project where data governance was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Evaluation, Analytics Engineering, Data Pipelines, Semantic Layer Design, and Data Governance. 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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