Global Director, AI, Data, & Emerging Technology Advancement

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title as heading. Must not include Job ID etc. Must preserve all substantive info, remove boilerplate. We need to parse the posting. First paragraph: description of role. That could be "About the role". Use

About the role

then

with that description. Then "PRINCIPAL ACCOUNTABILITIES" with subheadings: Data Foundation (with bullet points) and AI, Automation, Emerging Technology & Self-Service (with bullet points) and Enablement & Training, Risk & Compliance Partnership, Center of Excellence, Cross-Functional Partnership. Those are responsibilities. So we can put

Responsibilities

then

• each bullet. We need to preserve all details. Let's extract bullet points. From "Data Foundation" section: - 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. Then "AI, Automation, Emerging Technology & Self-Service" section: - 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. Then "NATURE AND SCOPE": reports to Global VP, member of IT leadership team, influences senior leaders, partners with regional business teams, leads a globally dispersed team of approx 6 to 10 professionals, expected to expand, accountable for AI, Data, and Automation strategy, architecture, governance, capability, owns associated multi-year roadmap, operating and capital budget, tools ecosystem, vendor relationships. That could be part of Responsibilities or maybe a separate section like "Scope". But we only have allowed headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We could incorporate nature and scope into Responsibilities or About the role. Probably Responsibilities. Then "WHAT SUCCESS LOOKS LIKE IN THE FIRST YEAR": bullet points of success metrics. Could be part of Responsibilities or maybe a separate "Expectations". But we can include under Responsibilities as additional bullet points. Then "KNOWLEDGE & SKILLS": list of requirements. That's Requirements/Knowledge & Skills. We'll put under

  Requirements

  (or Qualifications?). The spec says we can use Requirements, Qualifications, Skills sections. We need to decide where to put each piece. The list includes years of experience, direct experience, hands-on MDM, experience with Microsoft 365 Copilot, knowledge of data privacy, experience building governance framework, experience with self-service BI/analytics platforms, experience with enterprise data platforms in SAP environment (plus), manufacturing experience (plus), comfort operating as builder, communication style. That's a mix of requirements and qualifications. We could put under Requirements (or Qualifications). Since we have both sections, we could separate: Requirements = years of experience, direct experience, hands-on MDM, experience with tools, etc. Qualifications = pluses (SAP, manufacturing). Skills = communication style, builder mindset. But spec says prefer few substantive sections over many thin ones. So maybe combine all into Requirements. But we need to follow instruction: "Use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't require us to use all; we can use only those with real content. We could have About the role, Responsibilities, Requirements (including knowledge & skills), Benefits, Pay. Schedule not mentioned, so omit. Pay: we have "BAC Hiring Compensation Range $154,100- $264,000". That's pay. So include Pay section. Benefits: "BAC offers a comprehensive benefits package to include medical, dental, vision, paid time off, 401k, employee stock ownership plan, and more. Please see additional details on the BAC website at www.Baltimoreaircoil.com. BAC Employees are eligible to participate in an annual bonus incentive program." That's benefits. So include Benefits. Schedule: not mentioned, omit. Now we need to ensure we don't include boilerplate like Equal Opportunity Employer, etc. Remove. Now craft HTML. Structure:

  About the role

  ... (description)

  Responsibilities

  • ... each bullet
  ...

  Requirements

  • ... each bullet from Knowledge & Skills (maybe split into sub-bullets? but we can keep as list items)

  Benefits

  • Medical, dental, vision, paid time off, 401k, employee stock ownership plan, and more.
  • Annual bonus incentive program eligibility.
  Maybe also mention website but that's reference; could include as

  See details at www.Baltimoreaircoil.com.

  but that's not a benefit per se. We'll keep as

  For more details, see the BAC website at www.Baltimoreaircoil.com.

  Pay

  Compensation range: $154,100 – $264,000.

  We must not repeat job title. Ensure no extra headings. Now we need to preserve all substantive information. Let's verify we didn't miss any. From About the role: The first paragraph: "The Director, AI, Data, and Emerging Technology Advancement is a new leadership role within the Global Business Systems (herein referred to as “GBS”) team and is responsible for building BAC (Baltimore Aircoil Company, Inc.)’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." We'll put that in About the role. Now Responsibilities: need to include all bullet points from Principals Accountabilities plus Nature and Scope plus What Success Looks Like. Let's list them: Data Foundation bullets (6) AI, Automation, Emerging Technology & Self-Service bullets (9? Actually we have: AI & Analytics Strategy, AI Governance, Automation, Self-Service Analytics, Emerging Technology, Enablement & Training, Risk & Compliance Partnership, Center of Excellence, Cross-Functional Partnership) that's 9. Nature and Scope bullets: - Reports to Global VP, Chief Digital & Information Officer and member of IT leadership team. - Influences senior leaders across enterprise and partners closely with regional business teams. - Leads a globally dispersed team of approx 6 to 10 professionals, including internal employees and contracted resources, expected to expand. - Accountable for AI, Data, and Automation strategy, architecture, governance, capability; owns associated multi-year roadmap, operating and capital budget, tools ecosystem, vendor relationships. What Success Looks Like in the First Year bullets: - Documented enterprise data strategy and target-state data architecture, aligned with Enterprise Architecture. - Master data governance stood up for at least one or two critical domains, with clear ownership and stewardship. - Published AI governance framework and acceptable use policy deployed across enterprise. - Measurable reduction in stale, unstructured, duplicate, and over-permissioned data reachable by AI tools like Copilot and others. - Self-service analytics platform and support model with real adoption, reducing backlog of ad hoc reporting requests to IT. - Training program with completion and usage metrics tracked. - Several automation use cases delivered end-to-end, and plan to scale further. We should include all. Now Requirements: from Knowledge & Skills list: - 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 how data should flow, be owned, and be governed across a multi-system landscape. - Hands-on master data management (MDM) experience, designing governance for critical data domains (customer, product, vendor, materials, or similar) and standing up business stewardship models. - Experience with Microsoft 365 Copilot (and other popular AI tools), governance and the surrounding data governance toolset (e.g., Purview, SharePoint Advanced Management, Restricted Content Discovery, or equivalents). - Working knowledge of data privacy and compliance obligations relevant to a global manufacturer (e.g., GDPR and similar cross-border data regimes), and how to translate them into practical governance controls. - Practical experience building a governance framework from scratch, including policy, standards, and training, in an organization without a mature data or AI governance function already in place. - Experience with self-service BI/analytics platforms (e.g., Power BI, Tableau), data platform/MDM tooling (e.g., Purview, Informatica, SAP Master Data Governance), and process automation tools (e.g., Power Automate, UiPath). - Experience with enterprise data platforms in an SAP environment is a plus. - Manufacturing, industrial,