Nvidia Director Data Integration 

United States, California 

702454392

What you'll be doing:

• Take charge of the Data & Integration Engineering department, crafting and guiding platforms and services that facilitate data-informed decision-making throughout NVIDIA.

• Architect and operate enterprise data lakes, data warehouses, and data platforms that power analytics, AI training, and inference.

• Define and deliver end-to-end data pipelines—from ingestion and curation to analytics and visualization.

• Build enterprise Power BI and self-service analytics capabilities, ensuring employees and leaders have timely, accurate, and actionable insights.

• Establish data integration frameworks that connect enterprise systems, AI models, and B2B ecosystems (partners, suppliers, customers).

• Ensure secure, governed, and compliant data exchange with external entities to support business operations, supply chain, and partner collaboration.

• Encourage the adoption of AI and ML in data engineering and integration, encompassing intelligent transformations, anomaly detection, and predictive insights.

• Drive the architecture of event-driven integrations (e.g., APIs, Kafka, service mesh) to support real-time business workflows.

• Collaborate with business collaborators to speed up time-to-insight and unlock value from enterprise data for both internal and B2B use cases.

• Recruit, mentor, and grow a distributed team of engineers passionate about data platforms, APIs, integration, and BI/analytics.

What we need to see:

• 15 or more overall years of expertise in data engineering, integration, or distributed systems, including a minimum of 5 years in a senior management role.

• BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience).

• Demonstrated achievement in crafting and operating large-scale data platforms for enterprises, encompassing data lakes, warehouses, Lakehouse, and cloud-native data ecosystems.

• Strong technical background in integration technologies (e.g., Kafka, event streaming, API gateways, service mesh, iPaaS).

• Experience leading data governance, metadata management, and observability initiatives.

• Solid understanding of cloud platforms (AWS, GCP, Azure) and modern data stacks.

• Familiarity with AI/ML pipelines, model training, deployment, and serving.

• Ability to translate business priorities into data and integration strategies.

• Strong leadership, communication, and cross-functional collaboration skills.