Senior Analytics Engineer, Finance

- 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.

- 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.

- 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.

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:

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.

- 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:

- 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.

- 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/

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.

- 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.

- 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.