Director, Data Engineering

We are seeking a visionary Director, Data Engineering to architect the "data set of the future." This role is not just about reporting; it is about building the scalable, AI-ready infrastructure that will fuel our next generation of manufacturing innovation. You will move the organization beyond traditional data warehousing to a robust Data Lakehouse architecture, ensuring our enterprise data—from shop floor to point-of-sale—is clean, real-time, and ready for advanced GenAI and predictive modeling.

The ideal candidate is a technologist who fluently bridges the gap between the plant floor and the front office. You will be responsible for integrating complex operational data with high-velocity sales and commercial data to create a unified ecosystem. By connecting factory efficiency directly to customer demand and market trends, you will enable us to pivot from reactive operations to a truly predictive enterprise.

Key Responsibilities:

• Architecting the Future: Define and execute a data infrastructure roadmap centered on a Lakehouse architecture that integrates structured and unstructured data, enabling both real-time operational analytics and high-scale AI/ML workloads.
• AI-Ready Foundation: Establish the data governance, cataloging, and lineage frameworks necessary to power secure, trusted AI models and Large Language Models (LLMs) across the enterprise.
• Manufacturing Integration: Partner with OT and Engineering teams to ingest and operationalize IIoT and supply chain data, creating a unified data ecosystem that drives predictive maintenance and factory floor efficiency.
• Modern Data Stack Leadership: Oversee the transition from legacy BI tools to modern, self-service analytics platforms, ensuring the organization has the agility to derive insights from the data lakehouse.
• Data Ops & Governance: Lead the transition to MLOps and DataOps methodologies, ensuring data quality, security, and compliance in an increasingly automated environment.
• Strategic Partnership: Collaborate with business unit leaders to identify and prioritize data products that drive measurable top-line growth or operational cost reductions.
• Team Leadership: Build and mentor a high-performing team of data engineers, ML engineers, and data architects who are comfortable in both cloud-native environments and complex legacy manufacturing systems.