Senior Data Platform Engineer: Ingestion, Spark & Data Quality

NVIDIA Corporation; Santa Clara (CA); On-site; USD 200,000 - 322,000; Full time

Benefits offered by this job

Equity and benefits

Job summary

NVIDIA's DGX Cloud organization is seeking a Senior Data Engineer to join its data team. You will own major platform components such as ingestion, data quality, or serving, driving architecture, plan, and production results.

You will lead cross-team delivery, clarify requirements, and mentor engineers while coding and debugging. Our stack centers on Python, SQL, Databricks, and Spark, with emphasis on scalable data products for fleet health, capacity, utilization, and cost.

Qualifications

• Proven track record building and operating production software and data platforms.
• Experience owning a major component from requirements to release and operation.
• Strong understanding of data pipelines, batch/streaming, and data quality.
• Experience with Databricks, Spark, SQL, and data modeling for analytical consumption.

Responsibilities

• Own a major platform component and its roadmap, defining architecture and interfaces.
• Lead technical delivery across teams, clarify requirements, and manage risks.
• Build data pipelines for fleet, capacity, utilization, and cost data.
• Develop shared platform capabilities and onboarding, tooling, and abstractions.
• Lead investigations spanning pipelines, SQL engines, and cloud services.
• Set quality, security, and operational standards and drive adoption.

Skills

Python

SQL

Spark

Data modeling

Distributed systems

Leadership

Technical leadership

Problem solving

Communication

Education

BS or MS in Computer Science, Engineering, or related field

Tools

Databricks

Spark

PySpark

Spark SQL

Delta Lake

Unity Catalog

Kubernetes

Airflow

Job description

NVIDIA's DGX Cloud organization is seeking a Senior Data Engineer to join its data team. You will own major platform components such as ingestion, data quality, or serving, driving architecture, plan, and production results.

You will lead cross-team delivery, clarify requirements, and mentor engineers while coding and debugging. Our stack centers on Python, SQL, Databricks, and Spark, with emphasis on scalable data products for fleet health, capacity, utilization, and cost.