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Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
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The Senior Data and Platform Engineer joins the DGX Cloud organization to build shared data infrastructure that transforms infrastructure telemetry and operational data into trustworthy data products. You will define the technical vision, architecture, and growth for a key data platform domain, transforming unclear requirements into well-defined systems. Day-to-day responsibilities include architecting and evolving batch and streaming systems to ingest and serve fleet, capacity, and cost telemetry. You will build shared platform capabilities like libraries, workflow abstractions, and deployment tooling while leading production investigations across pipelines, query engines, and distributed processing. Required skills include deep experience with distributed processing, relational or analytical databases, production ETL, and change-data capture. You must demonstrate proficiency in SQL, data modeling, and backend systems languages to ensure reliability, performance, and security across large GPU fleets.
Define and guide the technical vision, architecture, and growth for key DGX Cloud Data Platform domains.
Transform unclear requirements into well-defined architectures and personally write essential production code.
Architect and evolve batch and streaming systems to ingest and serve fleet telemetry at scale.
Build shared platform capabilities including libraries, workflow abstractions, and deployment tooling for cross-team use.
Lead high-impact production investigations to establish root causes and drive durable resolutions across distributed systems.
Establish engineering standards for automated testing, data quality, observability, and secure service identities.
Design robust data models, semantics, and serving interfaces to ensure trusted data is widely accessible.
Provide technical leadership through architecture reviews and hands-on mentorship of senior engineers.
What we're looking for
12+ years of relevant industry experience.
Bachelor’s degree or equivalent experience, and a Master’s degree or equivalent experience in Computer Science, Engineering, or a related field.
Sustained record of personally crafting, implementing, and operating production software, data platforms, databases, or distributed systems.
Hands-on experience with distributed processing, analytical or relational databases, production ETL, change-data capture, streaming, or backend and cloud systems.
Production proficiency in a backend or systems language with experience using data-processing and platform libraries.
Strong SQL and data-modeling skills including query execution, schema evolution, consistency, and cross-system correctness.
Experience establishing production safeguards such as automated testing, CI/CD, monitoring, alerting, and secure deployment.
Deep experience with distributed data processing and lakehouse architectures (preferred).