Principal Manufacturing & Semantic Architect

Title: Principal Manufacturing & Semantic Architect

Location: Remote, OH, US

Department: Corporate

Job Description:

Company Overview

Imagine Everything. Build the Future with Hexion.

At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress—developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future.

This is where bold thinkers, problem-solvers, and innovators come together to shape what’s next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward.

We don’t follow the status quo—we challenge it, disrupt it, and improve it. Every role at Hexion is part of something bigger.

We invest in innovation, sustainability, and continuous development—equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide.

Your Future Starts Here.  

If you’re ready to push limits, reimagine what’s possible, and create the extraordinary, Hexion is where you belong. 

Anything is possible when you imagine everything. 

Position Overview

The Principal Manufacturing & Semantic Architect is a critical leadership role responsible for defining and governing the canonical data and semantic model that underpins Hexion's industrial digital platform. 

This role will establish how manufacturing assets, processes, materials, and data are consistently represented across: 

• Plant systems (OT) 
• Enterprise systems (IT) 
• Cloud platforms 
• AI/ML models 
• Customer-facing applications 

The successful candidate will bring deep expertise in industrial standards (ISA-95 / ISA-88) and translate complex manufacturing environments into scalable, structured data models that enable interoperability, analytics, and AI.

Key Responsibilities

1. Define and Govern the Canonical Manufacturing Data Model 

Develop and maintain a standardized semantic model aligned with: 

• ISA-95 (enterprise-control integration) 
• ISA-88 (batch/process control) 
• Emerging industry standards (e.g., CFIHOS where applicable) 

Define core entities including: 

• Assets, equipment hierarchies, and locations 
• Materials, batches, and process segments 
• Operational states, events, and relationships 

Ensure consistent representation of manufacturing data across all systems. 

2. Establish Semantic Standards and Data Contracts 

Define and enforce: 

• Data schemas 
• API and event contracts 
• Naming conventions and units of measure 

Partner with engineering teams to ensure adherence across: 

• Edge systems 
• Cloud services 
• Integration layers 

Prevent semantic drift across teams, platforms, and external partners. 

3. Define Semantic Meaning and Canonical Structure of AI Features 

Define the semantic meaning and canonical structure of features used in predictive and optimization models. Establish what each feature represents in the context of manufacturing processes and operational data. 

• Define feature-level semantic definitions grounded in manufacturing domain knowledge 
• Ensure alignment between the meaning of training data and real-time operational data at the edge 
• Collaborate with data science teams to ensure models reflect real-world process behavior 

Note: The pipelines, storage, and lifecycle that deliver these features to AI models are owned by the Principal Industrial AI Data Architect. 

4. Provide Semantic Translation Between OT, IT, and Digital Platforms 

Serve as the authority on semantic and data model translation between: 

• Plant floor systems (PLC, DCS, SCADA, historians) 
• MES and ERP systems 
• Cloud-based data and application platforms 
• Ensure data models are both technically robust and operationally practical. 

Note: Technical connectivity and protocol-level integration with OT systems are owned by the Principal Edge & OT Architect. 

5. Support Platform Productization and External Solutions 

Design semantic models that ensure the data model scales across tenants, including: 

• Multiple manufacturing sites 
• Multi-tenant environments 
• External customer-facing products 

Ensure extensibility and long-term maintainability of the data model. 

Note: Data pipeline and access pattern design for multi-tenancy is owned by the Principal Industrial AI Data Architect. 

6. Lead Governance and Continuous Evolution 

Establish versioning and lifecycle management for: 

• Data models 
• Schemas 
• Semantic definitions 
• Facilitate cross-functional alignment across engineering, operations, and data teams. 

Serve as the final authority on semantic architecture decisions. 

7. Collaborate Across Teams 

Partner with: 

• Principal Edge & OT Architect (semantic model enforcement at the edge and OT data normalization) 
• Principal Industrial AI Data Architect (feature semantics and data pipeline alignment) 
• Platform Engineering (implementation of semantic standards in cloud services) 
• Plant Operations and Process Engineering teams (domain validation and real-world grounding) 

Ensure consistent execution across domains.

Key Competencies

• Strategic thinking with strong attention to detail 
• Ability to translate complex systems into structured models 
• Cross-functional leadership across OT, IT, and digital teams 
• Strong communication and stakeholder alignment skills 
• High ownership and accountability for architectural decisions

Minimum Qualifications

• Bachelor's degree in Engineering, Computer Science, Industrial Engineering, or related field (Master's preferred) 
• 10+ years of experience in manufacturing systems, industrial automation, or process engineering 
• 10+ years of experience in data modeling or system architecture in industrial environments 
• Demonstrated expertise in ISA-95 and ISA-88 standards and manufacturing data structures and hierarchies 
• Strong understanding of OT systems (PLC, DCS, SCADA, historians) 
• Strong understanding of MES and ERP integration patterns 
• Experience with relational and/or graph-based data modeling 

Preferred Qualifications

Experience with: 

• ISA or similar industry data standards 
• Industrial IoT platforms or edge-to-cloud architectures 
• AI/ML applications in manufacturing environments 
• Cloud platforms (AWS preferred) 

Familiarity with: 

• Time-series data and event-driven architectures 
• Data governance frameworks 

Leadership Expectations

• Operate as a thought leader in industrial data and semantic architecture

• Influence without direct authority across multiple teams and partners

• Drive standards adoption across internal and external stakeholders

• Balance long-term architectural vision with near-term delivery needs

Work Environment & Travel

Travel to manufacturing sites and partner locations as needed (~10–25%).

Other

We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law.

To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age.  Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.