[Hiring] Senior Data Engineer @NVIDIA

Role Description

NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud.

We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. You will work across various aspects to help make Navigator and the DGXC data platform a dependable source of truth.

What you'll be doing:

• Own systems end to end, from ambiguous customer and operational needs through architecture, implementation, deployment, observability, incident response, and ongoing support.
• Construct data pipelines and products, including designing and maintaining batch and streaming ingestion, transformation, reconciliation, and serving paths for fleet, capacity, utilization, cost, scheduling, and operational telemetry.
• Build shared libraries, workflow and DAG or equivalent experience abstractions to evolve the data platform.
• Engineer reliable distributed workloads and diagnose correctness and performance issues across applications, SQL engines, Spark jobs, storage systems, networks, and cloud services.
• Treat security as part of the build, applying least privilege, service identities, secrets management, access controls, environment isolation, auditability, and safe operational practices throughout the system lifecycle.
• Improve quality and operations by establishing automated tests, data-quality checks, lineage, freshness and completeness monitoring, actionable alerting, SLOs, and clear ownership.
• Deliver consumption experiences by making trusted data usable through well-modeled tables, APIs, automation, dashboards, and focused internal applications.
• Raise the engineering bar by leading build reviews, communicating tradeoffs, mentoring other engineers, and improving the team's architecture, testing, debugging, and operational practices.

Qualifications

• BS or MS in Computer Science, Engineering, or a related field, or equivalent experience.
• 5+ years of experience building and operating production software, data platforms, backend infrastructure, databases, or distributed systems.
• Strong software-engineering fundamentals and production proficiency in Python or another backend or systems language.
• Deep hands-on experience in at least one of the following areas:
  • Distributed data processing using Spark or a comparable compute framework.
  • Relational, distributed, or analytical database architecture and operation at scale.
  • Production ETL, change-data-capture, streaming, or event-processing systems.
  • Backend or cloud-platform systems that process, transform, or serve substantial data volumes.
  • Strong SQL and data-modeling skills, including a practical understanding of query performance, schema evolution, incremental processing, consistency, and analytical consumption patterns.
• Demonstrated ability to debug unfamiliar systems across multiple layers using logs, metrics, traces, query plans, profiles, and controlled experiments.
• Experience operating services or pipelines in a cloud or similarly complex production environment.
• Working knowledge of secure platform development, including identity and access management, least privilege, secret handling, trust boundaries, and safe multi-environment deployments.
• Ability to make sound architectural tradeoffs, own work through ambiguity, and communicate effectively with users, partner teams, and engineers from different fields.
• A track record of learning unfamiliar technologies and domains and turning that learning into maintainable systems and reusable team practices.
• Experience with AI agents and LLM-supported workflow automation, particularly as applied to engineering and operational activities.

Requirements

• Experience with Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, Unity Catalog, or another modern lakehouse or distributed-compute platform.
• Experience with Kafka or another streaming platform, change-data capture, event development, partitioning, consumer groups, offset management, or other high-volume event systems.
• Experience with scaling, migrating, or performance-tuning relational, distributed, time-series, object-storage, or search-focused data systems, including Elasticsearch or OpenSearch.
• Background working with AWS, Azure, GCP, Kubernetes, Slurm, compute clusters, GPU-accelerated infrastructure, or fleet-scale telemetry.
• Experience developing agentic systems, LLM-enabled workflow automation, harness engineering, or dependable evaluation and operational tooling for AI agents.

Benefits

• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
• The base salary range is 140,000 USD - 224,250 USD for Level 3, and 168,000 USD - 270,250 USD for Level 4.
• You will also be eligible for equity and benefits.