Principal Data & Platform Engineer

NVIDIA · Santa Clara, CA · 248,000 USD – 391,000 USD NVIDIA's DGX Cloud organization is looking for a lead expert in data and platform engineering to guide the building, creation, and management of the DGXC Data Platform. The Principal Data & Platform Engineer will transform complex operational needs into reliable platform services and shared datasets. Responsibilities: Define the architecture and multiyear technical roadmap, setting system boundaries, shared interfaces, and engineering standards across ingestion, processing, storage, and data serving. Lead delivery across platform engineers, data producers, and consumers. Build and operate reusable batch and streaming ingestion capabilities for service provider and internal data. Establish shared identifiers, data contracts, consistent modeling, and automated quality and certification capabilities. Guide cataloging, lineage, and governed access capabilities. Make onboarding and operations repeatable through shared libraries, reference implementations, deployment automation, and self-service workflows. Own production readiness and reliability standards. Mentor senior engineers and technical leads. Requirements: Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience. More than 16 years of progressively responsible experience developing and operating production software, data platforms, databases, or distributed systems. Extensive hands-on experience with distributed data processing, analytical databases, production ETL, streaming systems, or backend platforms. Strong software engineering fundamentals and production proficiency in Python or another backend or systems language. Deep SQL and data modeling expertise. Experience establishing production practices adopted by multiple teams. Nice to have: Extensive experience developing and managing Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, or Unity Catalog platforms. Experience delivering self-service data publishing, cataloging, lineage, data contracts, or certification systems. Experience combining operational data from various cloud providers and internal systems. Experience designing and operating Kafka or comparable streaming systems. Experience enabling AI agents to discover and use governed data.