Metrics Logs Traces Data Jobs

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Today

Senior Data Engineer - EDA Datacenter Analytics and Observability

NVIDIA Santa Clara, CA

Santa Clara, CA

Today

$184k - $357k/yr Full time Senior Analytics Big Data

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Job Description

NVIDIA is building analytics-ready data platforms that turn complex observability and telemetry into trusted datasets for observability, reliability analysis, and capacity forecasting for EDA datacenters. In this hybrid role in Santa Clara, CA, you will design and evolve pipelines that help teams move from raw metrics, logs, traces, and hardware health signals to analytics and predictive insights at scale.

What you’ll do

Design, build, and maintain analytics-focused data pipelines to ingest, transform, and curate observability data from EDA datacenters
Create reliable ingestion pipelines for metrics, logs, traces, and hardware health telemetry produced by large-scale CPU and GPU clusters
Partner with observability engineers to integrate data from Prometheus, Grafana, Elastic/OpenSearch, and Spark into unified analytical datasets
Model and organize data to support exploratory analysis, reliability modeling, forecasting, and long-term trend analysis
Build and optimize batch and streaming workflows for near-real-time analytics and historical analysis
Implement data quality checks, validation frameworks, and monitoring to support analytical accuracy and consistency
Define data retention, aggregation, and enrichment strategies that balance analysis needs, performance, and storage costs
Improve data discoverability, documentation, and usability to support self-service analytics
Work with data scientists and analysts to understand requirements and evolve datasets for new models and insights
Continuously improve pipeline scalability, reliability, and performance as datacenter footprint and workload complexity grow

What you’ll need

10+ years of experience designing, building, and operating large-scale data pipelines and data platforms for distributed systems or infrastructure data (MS preferred; BS acceptable with equivalent experience)
Proficiency in Python and SQL, including support for analytical and exploratory workloads
Hands-on experience with distributed data processing frameworks such as Spark (or similar)
Familiarity with observability and telemetry data, including metrics, logs, traces, and time-series data
Experience designing data models and schemas for flexible analysis and forecasting
Ability to take ownership of data engineering initiatives and drive them end-to-end with multi-functional partners
Experience implementing data quality, validation, and monitoring for analytics pipelines
Strong communication and collaboration skills, especially with engineering and infrastructure teams
Adaptability in fast-paced environments where analytical and operational needs evolve

Technologies you’ll work with

Python, SQL, Spark
Prometheus, Grafana, Elastic/OpenSearch
Time-series data, metrics, logs, traces

Compensation and benefits

Salary: USD 184,000 to 356,500 per year.

Benefits: equity and benefits.

Ways to stand out

Experience supporting datacenter infrastructure analytics, hardware reliability programs, or workload performance analysis
Familiarity with EDA workflows, HPC environments, or GPU-accelerated compute platforms
Experience integrating or operating observability stacks (Prometheus, Grafana, Elastic/OpenSearch, Kafka, Spark, or similar tools)
Background in large-scale distributed systems or data platforms
A track record of improving analytics velocity and reliability through better data foundations

Location: Santa Clara, CA (hybrid) #LI-Hybrid

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