Senior Software Engineer, Data Platform

at Nvidia

USD 168,000-322,000 per year

SENIOR

✅ On-site

Tech Stack
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.

AI AWS @ 4 Azure BI @ 4 Data Analysis Docker @ 4 ETL @ 4 Kubernetes @ 4 Machine Learning Parquet @ 4 Power BI @ 4 Protobuf @ 4 Python @ 7 Reporting @ 4 SQL @ 4 Spark @ 4 Tableau @ 4 Terraform @ 4

Details

The NVIDIA Operations organization is seeking an experienced software engineering professional to build data platforms and tools supporting data platform, reporting, and analytics initiatives. The role involves turning data into information that delivers insights and business results, including data tools used in testing semiconductor chips, boards, systems, and servers.

Responsibilities

Lead and plan data strategy initiatives with team members and IT based on data sources, data locations, and use cases.
Build, scale, and optimize self-service ETL frameworks and streaming pipelines for data storage and real-time analytics.
Design and implement framework modules to extract data from source systems, validate data integrity, apply business transformations, and store data in data lakes using AWS, Azure, and other platforms.
Enable self-service and machine learning platforms for individual business units.
Own data platform and transformation tools used in AI and machine learning.
Develop in-house tools for processing logs into data platforms, analytics, and custom visualizations for large-scale data analysis.

Requirements

Bachelor's or master's degree in Computer Science, Information Systems, or equivalent experience with programming knowledge.
7 or more years of relevant experience.
Experience defining and leading projects, collecting requirements, setting timelines, and delivering results.
Experience architecting, designing, developing, and maintaining data warehouses and data lakes for complex data ecosystems.
Strong Python experience, with a focus on data extraction and transformations.
In-depth experience developing ETL pipelines using Spark, SQL, and AWS or other cloud platforms.
Solid understanding of operational processes involving semiconductors, boards, systems, and servers.

Preferred Qualifications

Self-starter with a positive problem-solving outlook, ability to multitask, and strong organizational skills.
Working knowledge of Amazon Web Services, Kubernetes, Docker, and Terraform.
Experience with structured data formats such as Parquet and Protobuf, including schema evolution concepts.
Experience with semi-structured log parsing.
Experience integrating SAP systems, Datamarts, and BusinessObjects.
Experience with visualization tools such as Tableau, Power BI, and Jupyter Notebooks.

Compensation and Benefits

The base salary depends on location, experience, and compensation for similar positions. The base salary range is USD 168,000–270,250 for Level 4 and USD 200,000–322,000 for Level 5. The role also includes eligibility for equity and benefits.

Applications will be accepted at least until September 14, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.