Senior Data Engineer - EDA Datacenter Analytics and Observability

NVIDIA’s Hardware Infrastructure organization is seeking a Senior Data Engineer to build and evolve analytics-ready data platforms that power observability, reliability analysis, and capacity forecasting for EDA datacenters. In this role, you will focus on transforming large-scale observability and telemetry data into trusted, well-modeled datasets that enable data scientists, analysts, and engineers to drive insights across global CPU and GPU compute clusters. We work closely with observability, infrastructure, and data science teams to ensure that data from EDA workloads and datacenter hardware is high quality, accessible, and optimized for analytical and predictive use cases.What You’ll Be Doing:Design, build, and maintain analytics-focused data pipelines that ingest, transform, and curate observability data from EDA datacentersDevelop reliable ingestion pipelines for metrics, logs, traces, and hardware health telemetry generated by large-scale CPU and GPU clustersPartner with observability engineers to integrate data from tools such as Prometheus, Grafana, Elastic/OpenSearch, and Spark-based platforms into unified analytical datasetsModel and organize data to support exploratory analysis, reliability modeling, forecasting, and long-term trend analysisBuild and optimize batch and streaming workflows that support both near-real-time analytics and historical analysisImplement data quality checks, validation frameworks, and monitoring to ensure analytical accuracy and consistencyDefine data retention, aggregation, and enrichment strategies that balance analysis needs, system performance, and storage costsEnable self-service analytics by improving data discoverability, documentation, and usabilityCollaborate with data scientists and analysts to understand analytical requirements and evolve datasets to support new models and insightsContinuously improve pipeline scalability, reliability, and performance as datacenter footprint and workload complexity growWhat We Need to See:MS (preferred) or BS in Computer Science (or equivalent experience) or a related field with at least 10+ years of experience designing, building, and operating large-scale data pipelines and data platforms for distributed systems or infrastructure dataProficiency in Python and SQL, with experience supporting analytical and exploratory workloadsHands-on experience with distributed data processing frameworks such as Spark or similar technologiesFamiliarity working with observability and telemetry data, including metrics, logs, traces, and time-series dataExperience designing data models and schemas that support flexible analysis and forecastingAbility to take ownership of data engineering initiatives and drive them end-to-end in collaboration with multi-functional partnersExperience implementing data quality, validation, and monitoring for analytics pipelinesStrong communication and collaboration skills, particularly when collaborating with engineering and infrastructure teamsAdaptability in fast paced environments with evolving analytical and operational needsWays to Stand Out from the Crowd:Experience supporting datacenter infrastructure analytics, hardware reliability programs, or workload performance analysisFamiliarity with EDA workflows, HPC environments, or GPU-accelerated compute platformsExperience integrating or operating observability stacks (Prometheus, Grafana, Elastic/OpenSearch, Kafka, Spark, or similar tools)Background in large-scale distributed systems or data platformsA track record of improving analytics velocity and reliability through better data foundation#LI-HybridYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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.Applications for this job will be accepted at least until October 27, 2026.This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.SummaryLocation: US, CA, Santa Clara; US, MA, Westford; US, TX, Austin; US, OR, HillsboroType: Full time