Senior Analytics Engineer, Finance

D8 LooP; Santa Clara (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

NVIDIA in the United States seeks a Senior Analytics Engineer to drive end-to-end analytics for finance, designing semantic layers and dashboards in Tableau and Power BI, and building data apps on the Databricks Lakehouse. The role requires strong SQL, data modeling, data pipeline optimization, and governance to ensure high-quality, trusted data across platforms such as Databricks and Snowflake.

Collaborate with data engineers, leverage dbt, Airflow, and Jira to deliver reliable solutions and

Qualifications

• Strong SQL skills and proficiency in data modeling concepts (star schema, dimensional modeling, semantic design).
• Collaborate with data engineering teams to optimize data pipelines, ensure data quality, and improve data availability.
• Incremental loads: traditional data warehouse architectures; historical, snapshot, and incremental data processing patterns.
• Establish and implement data governance, validation rules, and transformation logic to ensure data consistency across systems including Unity Catalog policies within Databricks.
• Senior Analytics Engineer with end-to-end analytics capabilities spanning data engineering fundamentals, semantic layer design, dashboard development in Tableau and Power BI, and application development within Databricks.
• Finance domain knowledge; build semantic layers to develop consistent, well-governed analytical data models; deploy data applications on Databricks Lakehouse.

Skills

SQL

Data modeling

Data pipelines

Data quality

Incremental processing

Databricks

Unity Catalog

Tableau

Power BI

Spark

Python

R

dbt

Fivetran

Informatica

Data Factory

Airflow

Jira

Snowflake

Tools

Databricks

Tableau

Power BI

Jira

dbt

Fivetran

Informatica

Data Factory

Alteryx

Snowflake

Unity Catalog

Airflow

Job description

NVIDIA · nvidia.wd5.myworkdayjobs.com · checked today

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.

Skills, with evidence

• Strong SQL skills and proficiency in data modeling concepts (star schema, dimensional modeling, semantic design). must have
• Collaborate with data engineering teams to optimize data pipelines, ensure data quality, and improve data availability. must have
• Incremental loads 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. must have
• Governance & security Establish and implement data governance, validation rules, and transformation logic to ensure data consistency across systems including Unity Catalog policies within Databricks. must have · not practised here
• Spark 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.
• Warehousing 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.
• Airflow / orchestration Background with ETL/ELT tools (e.g., dbt, Fivetran, Informatica, Data Factory, Alteryx) and project tracking in Jira.
• Cost & performance Collaborate with data engineering teams to optimize data pipelines, ensure data quality, and improve data availability.
• Supervise and support interface health, error handling, and reconciliation processes, proactively resolving integration failures and data discrepancies.
• Python Exposure to data science tools or methodologies (Python, R, machine learning concepts, Snowflake).
• dbt Background with ETL/ELT tools (e.g., dbt, Fivetran, Informatica, Data Factory, Alteryx) and project tracking in Jira.
• Machine learning Exposure to data science tools or methodologies (Python, R, machine learning concepts, Snowflake). not practised here