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NVIDIA
NVIDIA

Pioneering accelerated computing and AI

Data Engineer, Document AI – Finance

职能数据工程
级别中级
地点United States, Canada, Santa Clara
方式现场办公
类型全职
发布1周前
立即申请

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.

NVIDIA is hiring a Data Engineer within the Finance AI and Data Science team. We are looking for an experienced Data Engineer to constantly innovate and turn complex challenges into high-performance pipelines that power our traditional analytics and modern agentic AI. Your role will involve ingesting and processing unstructured documents into our data platform, working closely with AI developers and finance experts to develop strong, scalable data products that convert raw text into actionable intelligence.

What you'll be doing:

  • Build and optimize pipelines that extract insights from complex financial documents like SEC filings, contracts, and tax reports. Use innovative tools and techniques to help humans and AI agents search and perform multi-step reasoning across different document types.

  • Combine business insight and the data engineering toolkit to support critical business process automation, BI, data science, and AI initiatives.

  • Trace data workflows to source systems, then develop and deploy accurate and optimized data pipelines, using modern scheduling, automation, and data orchestration tools.

  • Develop deep knowledge of financial data and requirements, working directly with collaborators and owning projects end-to-end on a diverse set of finance and finance-adjacent data sets.

  • Integrate AI into data workflows, applying sensible and secure agentic models as a core component of our data framework.

  • Deliver an audit-ready source of truth by implementing strict data quality and lineage standards, ensuring all technical solutions translate into clear, actionable insights for collaborators.

What we need to see:

  • Bachelor's or Master’s in a quantitative field such as Statistics, Computer Science, Business Analytics, Data Science, Economics, or equivalent experience.

  • 5+ years of experience, with at least 4 years in data engineering.

  • ETL/ELT experience in modern Data Platforms such as Snowflake, Databricks, or AWS/Azure/GCP equivalents is required. Experience with Git and building and maintaining CI/CD pipelines is also needed. Familiarity with orchestrators like Airflow and testing tools like pytest or Great Expectations is important.

  • Ability to write readable and maintainable code (primarily in SQL, Python/Py Spark), knowledge of scientific libraries for data processing (Numpy, Sci Py, Pandas).

  • Experience collaborating with IT, Info Sec, business partners, and data scientists to build end-to-end data pipelines that ensure data accuracy and quality across relational databases, data lakes, and warehouses.

  • A passion for data engineering backed by a basic understanding of statistics and machine learning, with the communication skills necessary to translate technical status to diverse collaborators.

Ways to stand out from the crowd:

  • Experience with SAP and/or Salesforce.

  • Practical experience building and deploying Graph-RAG and similar systems, using a wide variety of data formats (e.g., JSON, XML, PDF, Word, Excel, PowerPoint, etc.).

  • Experience assisting a data science group centered on business functions (finance, sales ops, HR, marketing, supply chain, etc.).

  • Experience with app development frameworks like Flask and/or Streamlit, data versioning tools like DVC, and data processing tools like dbc.

  • Familiarity with regulated data, and building pipelines with compliance requirements.

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 the pay of employees in similar positions. The base salary range is 152,000 USD - 230,000 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 26, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

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关于NVIDIA

NVIDIA

NVIDIA

Public

A computing platform company operating at the intersection of graphics, HPC, and AI.

10,001+

员工数

Santa Clara

总部位置

$4.57T

企业估值

评价

10条评价

4.4

10条评价

工作生活平衡

2.8

薪酬

4.5

企业文化

4.2

职业发展

4.3

管理层

3.8

78%

推荐率

优点

Cutting-edge technology and innovation

Excellent compensation and benefits

Great team culture and collaboration

缺点

High pressure and expectations

Poor work-life balance and long hours

Fast-paced environment leading to burnout

薪资范围

79个数据点

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

7份报告

$170,275

年薪总额

基本工资

$130,981

股票

-

奖金

-

$155,480

$234,166

面试评价

5条评价

难度

3.0

/ 5

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience