Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Marketing @ 3
Python @ 3
SQL @ 3
Statistics @ 3
GCP @ 3
ETL @ 3
Airflow @ 2
CI/CD @ 3
Machine Learning @ 6
Data Science @ 3
Hiring @ 3
AWS @ 3
Azure @ 3
Communication @ 6
Data Engineering @ 3
Flask @ 3
Git @ 3
PyTest @ 2
ELT @ 3
BI @ 3
JSON @ 3
XML @ 3
Databricks @ 3
Snowflake @ 3
Audit @ 3
Compliance @ 2
Pandas @ 3
Salesforce @ 3
AI @ 3
Agentic AI @ 3
RAG @ 3
Data Pipelines @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today were tapping into the unlimited potential of AI to define the next era of computing. NVIDIA is hiring a Data Engineer within the Finance AI and Data Science team to innovate and build high-performance pipelines that power traditional analytics and modern agentic AI. The role focuses on ingesting and processing unstructured financial documents into the data platform and building scalable data products that convert raw text into actionable intelligence.
Responsibilities
- Build and optimize pipelines that extract insights from complex financial documents like SEC filings, contracts, and tax reports. Enable search and multi-step reasoning across document types for humans and AI agents.
- Combine business insight and data engineering tools to support business process automation, BI, data science, and AI initiatives.
- Trace data workflows to source systems and develop and deploy accurate, optimized data pipelines using modern scheduling, automation, and data orchestration tools.
- Develop deep knowledge of financial data and requirements; own projects end-to-end across finance and finance-adjacent datasets.
- Integrate AI into data workflows, applying sensible and secure agentic models as a core component of the data framework.
- Deliver an audit-ready source of truth by implementing strict data quality and lineage standards so technical solutions translate into clear, actionable insights.
Requirements
- Bachelors or Masters in a quantitative field (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 on modern data platforms such as Snowflake, Databricks, or AWS/Azure/GCP equivalents.
- Experience with Git and building/maintaining CI/CD pipelines.
- Familiarity with orchestrators like Airflow and testing/tools such as pytest or Great Expectations.
- Ability to write readable, maintainable code primarily in SQL and Python/PySpark; knowledge of scientific/data libraries (NumPy, SciPy, pandas).
- Experience collaborating with IT, InfoSec, business partners, and data scientists to build end-to-end pipelines across relational databases, data lakes, and warehouses.
- Basic understanding of statistics and machine learning and strong communication skills to translate technical status to diverse collaborators.
Ways to Stand Out
- Experience with SAP and/or Salesforce.
- Practical experience building and deploying Graph-RAG and similar systems, using varied data formats (JSON, XML, PDF, Word, Excel, PowerPoint).
- Experience supporting data science groups for business functions (finance, sales ops, HR, marketing, supply chain).
- Experience with app frameworks like Flask or Streamlit, data versioning tools like DVC, and data processing tools like dbc.
- Familiarity with regulated data and building pipelines that meet compliance requirements.
Compensation and Benefits
- Base salary ranges provided by level:
- Level 3: 152,000 USD - 230,000 USD
- Level 4: 168,000 USD - 264,500 USD
- You will also be eligible for equity and benefits. See www.nvidiabenefits.com and https://www.nvidia.com/en-us/benefits/ for details.
Additional Information
- 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 an equal opportunity employer committed to fostering a diverse work environment.