Principal Manufacturing & Semantic Architect

Hexion Careers • Remote, OH

3d • Hybrid

About The Position

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, and 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.

Requirements

• 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
• 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

Nice To Haves

• 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
• Familiarity with Data governance frameworks

Responsibilities

• Define and Govern the Canonical Manufacturing Data Model: Develop and maintain a standardized semantic model aligned with ISA-95 (enterprise-control integration) and ISA-88 (batch/process control), and 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.
• Establish Semantic Standards and Data Contracts: Define and enforce Data schemas, API and event contracts, and Naming conventions and units of measure. Partner with engineering teams to ensure adherence across Edge systems, Cloud services, and Integration layers. Prevent semantic drift across teams, platforms, and external partners.
• 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.
• 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, and Cloud-based data and application platforms. Ensure data models are both technically robust and operationally practical.
• Support Platform Productization and External Solutions: Design semantic models that ensure the data model scales across tenants, including Multiple manufacturing sites, Multi-tenant environments, and External customer-facing products. Ensure extensibility and long-term maintainability of the data model.
• Lead Governance and Continuous Evolution: Establish versioning and lifecycle management for Data models, Schemas, and Semantic definitions. Facilitate cross-functional alignment across engineering, operations, and data teams. Serve as the final authority on semantic architecture decisions.
• 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), and Plant Operations and Process Engineering teams (domain validation and real-world grounding). Ensure consistent execution across domains.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal