[Hiring] 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.

Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform.

You will be responsible for the architecture, technical plan, and production results of a major platform area like ingestion and orchestration, data quality and reconciliation, or data serving and consumption. You will clarify requirements with customers, define technical objectives, guide design and development among engineers and partner teams, and stay actively engaged in coding, debugging, and production tasks.

Successful candidates have already led complex technical work across team boundaries and delivered improvements that other groups adopted. Our primary implementation environment is Python, SQL, Databricks, and Spark.

What you’ll be doing:

• Own a major platform component and its roadmap, defining architecture, interfaces, technical goals, and evolution.
• Anticipate capacity, compatibility, and operational needs over a multi-year horizon, translating them into achievable breakthroughs.
• Lead technical delivery across teams, clarifying vague requirements and breaking down design and implementation work.
• Establish release turning points and manage dependencies and delivery risks.
• Guide the work process, revise plans when requirements shift, and keep management and partner teams informed and aligned.
• Build data pipelines and products, planning and carrying out batch and streaming ingestion, transformation, reconciliation, and serving processes.
• Establish data models and agreements that remain stable as sources, consumers, and scale progress.
• Develop shared platform capabilities, directing the creation and adoption of libraries, workflow and DAG abstractions, and standard implementation approaches.
• Lead complex production investigations, serving as the technical point of accountability for issues spanning various components.
• Define quality, security, and operational expectations, establishing and implementing testing, data-quality, reconciliation, lineage, SLO, and release-readiness standards.
• Make trusted data usable by delivering well-modeled tables, APIs, automation, dashboards, and focused internal applications.
• Provide technical leadership through others by guiding design reviews and mentoring engineers.

Qualifications

• BS or MS in Computer Science, Engineering, or a related field (or equivalent experience), and at least 12+ years of equivalent experience.
• A sustained record of building and operating production software, data platforms, databases, or distributed systems.
• Proven ability to outline a component’s technical plan, establish objectives for engineers, and guide delivery.
• Extensive practical experience in distributed processing using Spark or similar systems, relational databases, production ETL, or backend platforms.
• Strong software-engineering fundamentals and production proficiency in Python or another backend language.
• Strong SQL and data-modeling skills, with practical depth in query execution and schema evolution.
• Experience leading complex investigations involving multiple components and teams.
• Demonstrated architectural judgment and experience leading significant migrations or architectural changes.
• Experience establishing production quality and operational practices that other engineers adopt.
• Proven success in influencing technical decisions and advancing workflow improvements across teams.

Requirements

• Proven expertise in building, refining, and running Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, or Unity Catalog workloads.
• Experience designing and operating Kafka or comparable streaming systems.
• Experience scaling, migrating, or tuning relational, distributed, or time-series systems.
• Background operating compute or GPU clusters, or working with Kubernetes, Slurm, cloud infrastructure.
• Experience building production agentic systems, including tool integration and observability.

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 200,000 USD - 322,000 USD.
• You will also be eligible for equity and benefits.