Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Santa Clara, CA, US
Live, first seen by us 86 days agoWith competitive salaries and a generous benefits package, we are widely considered to be one of the world's most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5. You will also be eligible for equity and benefits.Read the full posting
Work setup in the employer’s posting: TELECOMMUTEFrom the employer’s posting
Employment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
Integrate NVIDIA data processing libraries into real query engines and OLAP databases, from prototype to measured…
Design and run TPC-H, TPC-DS, and ClickBench benchmarks against strong CPU baselines
Define the integration surface between NVIDIA libraries and third-party query engines, including plan handoff and…
Provide reference implementations, integration guides, and hands-on help to developers and partners
Track the analytical data processing ecosystem and share findings with NVIDIA engineering, product, and field teams
Demonstrate and integrate NVIDIA's data processing stack (libraries, SDKs, and tools) into real query engines and OLAP databases
Design and run TPC-H, TPC-DS, and ClickBench measurements against the strongest available CPU baselines
Define the integration surface between NVIDIA's GPU data processing libraries and third-party query engines
providing working reference implementations, integration guides, and direct hands-on engineering help
Track the analytical data processing ecosystem: new engines, execution models, storage formats, and competing approaches to acceleration
What We Need to See: * Bachelor's or Master's degree or equivalent experience in Computer Science, Engineering, or a related field. * 6+ years of overall professional experience in the technology industry in software engineering, developer relations, technical partnerships, solutions architecture, or product management, including hands-on experience with analytical data systems. Equivalent evidence of domain authority is weighed in place of years: published systems research, maintainership of a widely used data system, or core contributions to a query engine or data processing library.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Day 86
Up longer than most. Similar jobs usually come down between day 6 and day 55.
Well past NVIDIA’s usual: its jobs come down by about day 32.
From 13,214 similar postings that came down, and 106 of NVIDIA’s. Coming down is not always a hire.
104 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
* Experience working with or supporting open source data projects and their contributor communities, commercial data platform and database ISVs, or cloud service provider data services. * Working proficiency in the internals of analytical data systems: query execution and optimization, vectorized and columnar processing, joins and aggregation, and storage formats such as Parquet and Arrow. Comfortable reading and contributing to a large C++, Rust, or Python codebase. * Comfort collaborating with cross-functional teams to discuss architecture, share feedback, and deliver technical presentations or demos.
NVIDIA is building GPU acceleration for the analytical data processing ecosystem: the query engines, data platforms, and processing frameworks that the world runs its analytics on. Making that real means embedding an acceleration layer inside engines we do not own. Each of those engines has its own optimizer, scheduler, memory model, and exchange, and each one draws the line between "adopt your component" and "keep mine" in a different place. Nobody has settled what that integration surface should look like. That is the problem this role owns. We are looking for someone with genuine depth in how analytical data systems are built: query planning and processing, columnar and vectorized processing, storage formats, or the internals of a SQL engine. You will work with the maintainers, architects, and engineering leaders behind these systems, in public where the project is open and directly where it is not, on how acceleration lands in what they ship. You will produce the benchmark evidence that shows whether it worked, and turn what you learn into concrete requirements for NVIDIA's roadmap. This is a developer relations role rather than an engineering role because the leverage is breadth. An engineer improves one engine. This role shapes how acceleration lands across the ecosystem and influences which parts of it get there first.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
With competitive salaries and a generous benefits package, we are widely considered to be one of the world's most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5. You will also be eligible for equity and benefits.
Santa Clara, CA, US
* Build and deepen technical expertise in analytical data processing, including query execution and optimization, columnar and vectorized processing, and distributed execution. Serve as a technical advocate and trusted resource for the developers building and operating these systems, working with cross-functional partners to drive adoption of NVIDIA technologies such as Sirius, cuCascade, RAPIDS, cuDF, nvCOMP, and CUDA-X Data Processing. * Demonstrate and integrate NVIDIA's data processing stack (libraries, SDKs, and tools) into real query engines and OLAP databases, carrying the work from prototype through to a functioning, measured integration across cloud, hybrid, and on-prem deployments. * Support developers, projects, and partners through onboarding and integration by providing working reference implementations, integration guides, and direct hands-on engineering help, so that a first integration produces a real accelerated query path rather than a demo.
No clear work-authorization passage found. Eligibility is unconfirmed.