Manager, Data and AI Engineering

Details

We are looking for a Manager of Data & AI Engineering who combines deep technical expertise with strong delivery leadership and people management. This role will drive the build-out of a next-generation autonomous data intelligence platform for Supply Chain Operations—from identifying high-impact opportunities to architecting, building, and productionizing solutions that deliver measurable business value. The ideal candidate brings hands-on experience in architecture and engineering while demonstrating the ability to manage a high-performing team. This person will partner with business collaborators, translate operational challenges into data and AI solutions, and deliver at pace.

Responsibilities

• Design and build scalable data and AI platforms using Databricks, AWS, and modern cloud-native engineering patterns.
• Deliver robust ETL/ELT, streaming, and CDC pipelines using technologies such as Spark, Kafka, Delta Lake, and AWS-native services.
• Enable AI-powered use cases, including RAG applications, AI agents, tool-calling workflows, and data-driven web applications.
• Design data models using Star Schema, Snowflake Schema, and Data Vault patterns appropriate to the use case, optimizing for analytical query performance, data governance, and extensibility.
• Implement data quality frameworks, observability, alerting, and monitoring to ensure pipeline integrity and production reliability.
• Build the data foundation for GenAI, agentic AI, and advanced analytics initiatives, including RAG pipelines, vector search, knowledge graphs, and multi-agent orchestration patterns.
• Partner with product, business, analytics, and AI collaborators to translate requirements into secure, scalable, and production-ready solutions.
• Oversee resource planning, prioritization, project execution, and delivery across multiple concurrent initiatives.
• Mentor engineers, grow technical capability across the team, and develop a culture of accountability, innovation, and continuous improvement.
• Provide hands-on technical leadership across architecture, design reviews, implementation guidance, and production readiness.
• Handle the full lifecycle of data engineering projects, from discovery and planning through execution and production rollout.

Requirements

• Master's or Bachelor's degree in Computer Science or Information Systems, or equivalent experience.
• 10+ overall years of experience in data engineering, software engineering, or web application development, with at least 3+ years specifically in a leadership or engineering management role.
• Willingness to code, including writing code, prototyping, and building production systems alongside the team.
• Intimate knowledge of the AWS ecosystem, including Amazon S3, EC2, IAM, Lambda, and API Gateway.
• Proven experience operationalizing Large Language Models (LLMs) into autonomous agents that can plan, use tools, and implement multi-step workflows.
• Proven deep expertise in Apache Spark, PySpark, Delta Lake, and Databricks Workflows.
• Hands-on experience scaling Unity Catalog is highly preferred.

Preferred Qualifications

• Active Databricks certifications, such as Data Engineer Professional or Generative AI Engineer Associate.
• Active AWS certifications, such as Certified Data Engineer—Associate or Solutions Architect—Professional.
• Experience managing multifunctional teams that combine data engineers with front-end and back-end software developers.
• Knowledge of supply chain business processes for Plan, Make, Deliver, and Services.

Compensation and Benefits

• Base salary range: USD 200,000–322,000, determined based on location, experience, and the pay of employees in similar positions.
• Eligible for equity and benefits.
• Applications will be accepted at least until August 2, 2026.

NVIDIA uses AI tools in its recruiting processes and is committed to fostering an inclusive work environment and providing equal employment opportunities.