Global Director, AI, Data

Baltimore Aircoil Company, BAC, is a global manufacturer of heat transfer products and services. We specialize in developing resource-saving evaporative cooling equipment that conserves water and energy. The products of BAC Europe are distributed across Europe, the Middle – East and North Africa.

Function

To strengthen our EMEA HQ in Belgium, we’re recruiting an

In this role you are responsible for building BAC ’s strategy, architecture, governance, and capability across two connected areas: the foundational data that the business runs on, and the AI, automation, and self-service analytics capabilities built on top of it. This person owns data strategy end to end — architecture, master data governance, tooling, and compliance — and uses that foundation to define how the business uses AI and Emerging Technology tools and self-service analytics safely and effectively.

This is a build role at the intersection of strategy and hands‑on governance; accountable for getting the underlying data foundation right, then building the strategy, governance, and training that make safe, effective self‑service AI and analytics possible on top of it.

Principal Accountabilities

Data Foundation

• Data Strategy: define the enterprise data strategy: what data matters most to the business, how it should be organized and governed, and how the strategy sequences over time as the company grows.
• Data Architecture: own the enterprise data architecture: how data flows between SAP, custom applications, the MarTech stack, and analytics platforms, in partnership with Enterprise Architecture.
• Master Data Governance: Stand up master data governance for the enterprise's critical data domains (e.g., customer, product, vendor, materials). Define parameters for ownership, stewardship, quality standards, and the processes that keep master data trustworthy as it moves through SAP and downstream systems.
• Data Quality & Lifecycle: drive the ongoing effort to identify and remediate legacy, unstructured, duplicate, and over-permissioned data across the enterprise, partnering with business data owners.
• Data Tooling & Platform: evaluate, select, and govern the enterprise's data platform and tooling to manage data quality, cataloging, master data management, and integration.
• Data Compliance & Privacy: own the data governance controls that keep the enterprise compliant with data privacy and retention obligations, including cross-border data handling where relevant to the company's global footprint; partner with legal and compliance on data policies and with security on enforcement.

AI, Automation, Emerging Technology & Self-Service

• AI & Analytics Strategy: define the enterprise roadmap for self-service AI and analytics, including standard toolsets and guardrails, built on top of the data foundation strategy and tools.
• AI Governance: own the governance framework for AI use across the enterprise: acceptable use, data access boundaries, oversight of AI-surfaced content, security, and risk review for new AI use cases. Evaluate and deploy the tools that control what AI can see and surface, including restricted content discovery, M365 archive, SharePoint advanced management, and DLP.
• Automation: set the strategy and standards for process automation (RPA, workflow automation, low-code tools), self-service governance, monitoring, and maintenance.
• Self-Service Analytics: own the platform, standards, and support model for self-service analytics.
• Emerging Technology: own the evaluation and recommendation of emerging technologies to drive operational efficiency, enhance business effectiveness, and support digital transformation objectives.
• Enablement & Training: build and deploy the training and change management program for self-service AI, automation, and analytics tools.
• Risk & Compliance Partnership: work with security, legal, and compliance to make sure AI, automation, and data use stay within regulatory and privacy obligations as the program scales.
• Center of Excellence: stand up a lightweight data & AI center of excellence with champions, standards, and a support model that scales with adoption.
• Cross-Functional Partnership: partner closely enterprise architecture, infrastructure, and security to allow the data, AI, and automation strategy to leverage and enhance existing platform investments.

Profile

Knowledge & Skills

• 10+ years in data, analytics, or AI-related roles in enterprise IT, with 4+ years in a leadership role owning data strategy and governance, delivery and reporting.
• Direct experience building enterprise data strategy and architecture — able to make and defend decisions about