Developer Relations Manager – Data Processing and Databases

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.

• 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, cu Cascade, 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.
• Track the analytical data processing ecosystem: new engines, execution models, storage formats, and competing approaches to acceleration. Share what you learn with NVIDIA engineering, product, marketing, and the worldwide field organization to shape adoption strategy.
• Collaborate with engine architects and NVIDIA engineering to resolve integration problems, establish best-practice patterns, and feed concrete technical requirements back to NVIDIA product teams.
• Define the integration surface between NVIDIA's GPU data processing libraries and third-party query engines: where the plan handoff occurs, how execution and memory ownership are divided, and which of a partner's differentiating components remain in place alongside ours. Specify the APIs NVIDIA must expose to make that possible, and carry the patterns that work forward from one integration to the next.
• Own the benchmark evidence for GPU-accelerated analytics. Design and run TPC-H, TPC-DS, and Click Bench measurements against the strongest available CPU baselines, separate cold and warm behavior, and publish results that hold up to outside scrutiny. Use those results to establish where the acceleration case is proven, where it is not yet, and what has to change.
• Own the acceleration roadmap jointly with the projects and partners you work with: what gets built, in what order, and which technical bets are worth making. Earn that standing where the work happens, through upstream contribution and public design review in open source, and through joint architecture and roadmap planning with partner engineering leadership.

• 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…