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 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, 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.
• Manage the full lifecycle of data engineering projects, from discovery and planning through execution and production rollout.

Requirements

• Bachelor's or Master's degree in Computer Science or Information Systems, or equivalent experience.
• 10+ years of overall experience in data engineering, software engineering, or web application development, including at least 4+ years in a leadership or engineering management role.
• Willingness to code, prototype, and build 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.
• 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 comprising data engineers and 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 per year, determined by location, experience, and the pay of employees in similar positions.
• Eligible for equity and benefits.
• Applications will be accepted at least until October 27, 2026.
• NVIDIA is an equal opportunity employer committed to fostering an inclusive work environment.