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NVIDIA

Developer Relations Manager – Data Processing, Databases

NVIDIA

Developer relations manager helping data-platform maintainers integrate NVIDIA GPU acceleration into query engines and OLAP databases. Defining APIs, validating performance, and shaping the acceleration roadmap.

Posted 8/10/2026full-timeRemote • California • 🇺🇸 United StatesMid-LevelSenior💰 $184,000 - $356,500 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in analytical data processing, including query execution and optimization, and has hands-on experience with NVIDIA technologies such as CUDA, RAPIDS, and cuDF. Capable of collaborating cross-functionally to drive integration and adoption of data processing solutions across various environments.

Highest-signal resume keywords
Analytical Data ProcessingQuery Execution And OptimizationNVIDIA Technologies (CUDA, RAPIDS, cuDF)Software EngineeringOpen Source Contributions

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Analytical Data SystemsQuery ExecutionVectorized ProcessingColumnar ProcessingC++RustPythonStorage Formats (Parquet, Arrow)Integration PatternsBenchmarking (TPC-H, TPC-DS)
Soft Skills
Strong Communication SkillsCollaborationProblem SolvingTechnical AdvocacyPassion For Developer Support
Tools & Technologies
NVIDIA Data Processing StackSiriusCuCascadeRAPIDSCuDFNvCOMPCUDA-X
Industry Keywords
Data ProcessingOLAP DatabasesCloud ServicesHybrid DeploymentsCommercial Data Platforms

Tech Stack

Tools & technologies
CloudOpen SourcePythonRust

About the role

Key responsibilities & impact
  • 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 developers building and operating analytical data systems.
  • Drive adoption of NVIDIA technologies including Sirius, cuCascade, RAPIDS, cuDF, nvCOMP, and CUDA-X Data Processing.
  • Demonstrate and integrate NVIDIA’s data processing stack into query engines and OLAP databases across cloud, hybrid, and on-prem deployments.
  • Provide reference implementations, integration guides, onboarding, and hands-on engineering support.
  • Track analytical data processing engines, execution models, storage formats, and competing acceleration approaches.
  • Share ecosystem insights with NVIDIA engineering, product, marketing, and worldwide field teams.
  • Collaborate with engine architects and NVIDIA engineering to resolve integration problems and establish best practices.
  • Define the integration surface between NVIDIA GPU data-processing libraries and third-party query engines.
  • Specify required APIs and carry successful integration patterns forward.
  • Design and run TPC-H, TPC-DS, and ClickBench measurements against CPU baselines.
  • Publish benchmark results, assess acceleration effectiveness, and identify required changes.
  • Own the acceleration roadmap jointly with projects and partners.
  • Earn ecosystem influence through upstream contributions, public design reviews, and joint architecture and roadmap planning.

Requirements

What you’ll need
  • 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.
  • Hands-on experience with analytical data systems.
  • Experience in software engineering, developer relations, technical partnerships, solutions architecture, or product management.
  • Equivalent evidence of domain authority may substitute for years of experience, including published systems research, maintainership of a widely used data system, or core contributions to a query engine or data processing library.
  • Experience working with or supporting open source data projects and contributor communities, commercial data platform and database ISVs, or cloud service provider data services.
  • Working proficiency in 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.
  • Ability to collaborate cross-functionally on architecture, feedback, technical presentations, and demos.
  • Ability to manage and implement technical projects and solve integration challenges.
  • Ability to communicate complex ideas to technical and non-technical audiences.
  • Strong communication skills and passion for helping developers innovate with NVIDIA tools and technology.
  • Preferred standout qualifications include open source committer, maintainer, or sustained contributor experience; shipped acceleration-layer or commercial data-platform integrations; published or presented systems work; partner engineering leadership experience; and familiarity with CUDA, RAPIDS, cuDF, nvCOMP, and CUDA-X libraries.

Benefits

Comp & perks
  • Competitive salaries
  • Generous benefits package
  • Equity
  • Benefits