Manager, Data and AI Engineering

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 our next-generation autonomous data intelligence platform for Supply Chain Operations , from identifying high-impact opportunities to architecting, building, and productionize 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 delivery of AI-powered use cases including RAG applications, AI agents, tool-calling workflows, and data-driven web apps.
• 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, and 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, and 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 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: You are still a builder at heart. You are excited to spend your time writing code, prototyping, and building production systems alongside your team.
• AWS Proficiency: Intimate knowledge of the AWS ecosystem, including Amazon S3, EC2, IAM, Lambda, and API Gateway.
• Agentic AI & LLM Mastery: Proven experience operationalizing Large Language Models (LLMs) into autonomous agents that can plan, use tools, and implement multi-step workflows.
• Databricks Mastery: Proven deep expertise in Apache Spark, PySpark, Delta Lake, and Databricks Workflows. Hands-on experience scaling Unity Catalog is highly preferred.

Nice to Have

• Active Databricks Certifications (e.g., Data Engineer Professional, Generative AI Engineer Associate).
• Active AWS Certifications (e.g., Certified Data Engineer – Associate or Solutions Architect – Professional).
• Background in managing multi-functional teams that blend data engineers with front-end and back-end software developers.
• Knowledge of supply chain business processes for Plan, Make, Deliver & Services