Senior Data Engineer - EDA Datacenter Analytics and Observability

Job Title

Senior Data Engineer - EDA Datacenter Analytics and Observability

Role Summary

Join NVIDIA's Hardware Infrastructure organization to design and operate analytics-ready data platforms that power observability, reliability analysis, and capacity forecasting for EDA datacenters. The role focuses on transforming large-scale telemetry (metrics, logs, traces, hardware health) from CPU and GPU clusters into trusted datasets for data scientists, analysts, and engineers.

The team partners with observability, infrastructure, and data science groups to ensure data quality, accessibility, and performance for analytical and predictive use cases.

Experience Level

Senior — requires substantial hands-on experience (typically 5+ years) designing, building, and operating large-scale data pipelines and platforms for distributed systems or infrastructure data.

Responsibilities

The role is responsible for building reliable, scalable analytics pipelines and datasets to support observability, forecasting, and reliability analyses.

• Design, build, and maintain analytics-focused pipelines that ingest, transform, and curate observability data from EDA datacenters.
• Develop reliable ingestion for metrics, logs, traces, and hardware telemetry from large-scale CPU/GPU clusters.
• Integrate data from observability tools into unified analytical datasets in partnership with observability engineers.
• Model and organize data to support exploratory analysis, reliability modeling, forecasting, and trend analysis.
• Build and optimize batch and streaming workflows for near-real-time and historical analytics.
• Implement data quality checks, validation frameworks, and monitoring to ensure accuracy and consistency.
• Define retention, aggregation, and enrichment strategies balancing analysis needs, performance, and storage cost.
• Improve data discoverability, documentation, and self-service analytics capabilities.
• Collaborate with data scientists and analysts to evolve datasets to meet new model and insight requirements.
• Continuously improve pipeline scalability, reliability, and performance as datacenter footprint grows.

Requirements

Key must-have technical skills and experience; followed by relevant nice-to-have qualifications.

• Must-have: At least 5+ years designing, building, and operating large-scale data pipelines and data platforms for distributed systems or infrastructure data.
• Proficiency in Python and SQL for analytical and exploratory workloads.
• Hands-on experience with distributed data processing frameworks (e.g., Spark).
• Experience working with observability and telemetry data (metrics, logs, traces, time-series).
• Experience designing data models and schemas to support flexible analysis and forecasting.
• Proven ability to own data engineering initiatives end-to-end with cross-functional partners.
• Experience implementing data quality, validation, and monitoring for analytics pipelines.
• Strong communication and collaboration skills; ability to adapt in a fast-paced environment.
• Nice-to-have: Experience with datacenter infrastructure analytics, hardware reliability programs, EDA workflows, HPC/GPU-accelerated platforms, or operating observability stacks (Prometheus, Grafana, Elastic/OpenSearch, Kafka).

Education Requirements

MS preferred or BS in Computer Science or a related field, or equivalent practical experience. Fields mentioned include Computer Science and related technical disciplines; the posting explicitly allows equivalent experience in lieu of degree.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.