Senior Data Engineer - Hybrid: Observability & Data Platforms

NVIDIA Corporation; United States; Hybrid; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Hybrid work arrangement

Job summary

NVIDIA Corporation is seeking a Senior Data Engineer to design and evolve analytics-ready data platforms powering observability, reliability analysis, and capacity forecasting for EDA datacenters. You will transform large-scale telemetry data into trusted datasets for data scientists, analysts, and engineers across global compute clusters.

You will build batch and streaming workflows, apply data quality controls, and work with Prometheus, Grafana, Elastic/OpenSearch, and Spark-based tools to

Qualifications

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

Responsibilities

• Design, build, and maintain analytics-focused data pipelines that ingest, transform, and curate observability data from EDA datacenters.
• Develop reliable ingestion pipelines for metrics, logs, traces, and hardware health telemetry generated by large-scale CPU and GPU clusters.
• Partner with observability engineers to integrate data from tools such as Prometheus, Grafana, Elastic/OpenSearch, and Spark-based platforms 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 that support both near-real-time analytics and historical analysis.
• Implement data quality checks, validation frameworks, and monitoring to ensure analytical accuracy and consistency.
• Define data retention, aggregation, and enrichment strategies that balance analysis needs, system performance, and storage costs.
• Enable self-service analytics by improving data discoverability, documentation, and usability.
• Collaborate with data scientists and analysts to understand analytical requirements and evolve datasets to support new models and insights.
• Continuously improve pipeline scalability, reliability, and performance as datacenter footprint and workload complexity grow.

Skills

Python

SQL

Spark

Observability data

Data pipelines

Education

MS or BS in Computer Science or related field

Tools

Prometheus

Grafana

Elastic/OpenSearch

Spark

Kafka

Job description

NVIDIA Corporation is seeking a Senior Data Engineer to design and evolve analytics-ready data platforms powering observability, reliability analysis, and capacity forecasting for EDA datacenters. You will transform large-scale telemetry data into trusted datasets for data scientists, analysts, and engineers across global compute clusters.

You will build batch and streaming workflows, apply data quality controls, and work with Prometheus, Grafana, Elastic/OpenSearch, and Spark-based tools to