Senior Data Engineer – Observability Analytics & Pipelines

NVIDIA Corporation; Santa Clara (CA); Hybrid; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

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.

You will transform large-scale telemetry data into trusted, well-modeled datasets enabling data scientists, analysts, and engineers to drive insights across global CPU and GPU compute clusters.

Qualifications

• MS (preferred) or BS in Computer Science (or equivalent) with 10+ years of experience in data pipelines and platforms for distributed systems.
• Proficiency in Python and SQL, with experience supporting analytical workloads.
• Hands-on experience with distributed data processing frameworks such as Spark.
• Familiarity with observability data, 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 end-to-end with cross-functional partners.
• Experience implementing data quality, validation, and monitoring for analytics pipelines.
• Strong communication and collaboration skills with engineering and infrastructure teams.
• Adaptability in fast-paced environments with evolving analytical needs.

Responsibilities

• Design, build, and maintain analytics-focused data pipelines ingesting observability data from EDA datacenters.
• Develop reliable ingestion pipelines for metrics, logs, traces, and hardware telemetry from large CPU/GPU clusters.
• Partner with observability engineers to integrate data from Prometheus, Grafana, Elastic/OpenSearch, and Spark-based platforms.
• Model and organize data to support exploratory analysis, reliability modeling, forecasting, and long-term trends.
• Build and optimize batch and streaming workflows for near-real-time and historical analytics.
• Implement data quality checks, validation frameworks, and monitoring for analytics accuracy.
• Define data retention, aggregation, and enrichment strategies balancing analysis needs and storage costs.
• Enable self-service analytics by improving data discoverability, documentation, and usability.
• Collaborate with data scientists and analysts to evolve datasets for new models and insights.
• Continuously improve pipeline scalability, reliability, and performance as datacenter footprint grows.

Skills

Python

SQL

Spark

Observability data

Data modeling

Data quality monitoring

End-to-end ownership

Collaboration

Education

MS or BS in Computer Science or related field

Tools

Prometheus

Grafana

Elastic/OpenSearch

Spark-based platforms

Job description

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.

You will transform large-scale telemetry data into trusted, well-modeled datasets enabling data scientists, analysts, and engineers to drive insights across global CPU and GPU compute clusters.