Industrial AI Data Architect — Real-Time Analytics Leader

Hexion; Columbus (OH); Remote; USD 140,000 - 210,000; Full time

Job summary

Hexion in Columbus, OH is seeking a Principal Industrial AI Data Architect to design and govern data architecture for reliable, scalable AI across industrial environments. You will bridge data, semantics, and AI execution to ensure consistent features and real-time analytics.

You will lead end-to-end data flows, feature pipelines, and multi-tenant data models, collaborating with AI, OT, and platform teams to turn business requirements into robust data infrastructure.

Qualifications

• Bachelor's degree in CS, engineering, or related field; Master's preferred.
• 10+ years in data architecture, industrial data systems, or IoT.
• Strong experience with time-series data and data pipelines.
• Understanding of AI/ML data requirements and feature engineering.
• Ability to influence across teams and drive standards.
• Willingness to travel 10–25%.

Responsibilities

• Define Industrial Data Architecture for AI and data flows.
• Design feature pipelines and delivery for AI models (training and inference).
• Integrate semantic model with data pipelines and schemas.
• Define data interfaces for internal AI teams and ensure data quality.
• Design for multi-tenant environments with secure access patterns and onboarding.

Skills

Industrial AI data architecture

Time-series data

Data pipelines

Feature engineering

Cross-functional leadership

Travel 10–25%

Education

Bachelor's degree in Computer Science, Engineering, or related field

Master's degree preferred

Tools

Historian systems

Distributed data systems

ETL/ELT tools

Job description

Hexion in Columbus, OH is seeking a Principal Industrial AI Data Architect to design and govern data architecture for reliable, scalable AI across industrial environments. You will bridge data, semantics, and AI execution to ensure consistent features and real-time analytics.

You will lead end-to-end data flows, feature pipelines, and multi-tenant data models, collaborating with AI, OT, and platform teams to turn business requirements into robust data infrastructure.