Principal Industrial AI Data Architect

This is a fully remote position, open to applicants in Ohio.

📋 Description

• Develop and oversee data architecture that facilitates dependable and scalable AI in industrial settings.

• Create comprehensive data flows from edge systems through cloud and AI pipelines to edge inference.

• Establish data storage patterns, data movement protocols, and transformation methodologies.

• Ensure that the architecture accommodates real-time processing, batch analytics, and integration of model lifecycles.

• Design and oversee feature pipelines, storage solutions, and lifecycle management for AI model features.

• Specify feature engineering pipelines for cloud-based training and edge inference applications.

• Maintain alignment between training datasets and runtime inference data.

• Mitigate feature drift and data discrepancies through automated validation processes.

• Convert canonical semantic definitions into tangible data models, schemas, and pipelines.

• Ensure that data structures adhere to enterprise standards and platform contracts.

• Define data interfaces for internal AI teams and external model providers.

• Support model versioning, feature compatibility, and performance validation efforts.

• Design data pipelines and access strategies for multi-tenant environments.

• Guarantee customer data isolation, secure access controls, scalable tenant onboarding, and reuse of pipelines.

• Collaborate with semantic architecture, edge and OT architecture, platform engineering, and AI/data science teams.

• Act as a thought leader and promote the adoption of data pipeline and AI data standards.

• Balance long-term architectural goals with immediate delivery requirements.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related discipline.

• Over 10 years of experience in data architecture, industrial data systems, or IoT platforms.

• Extensive experience with time-series data, particularly historian systems.

• Proficient in data pipelines and ETL/ELT processes.

• Strong background in distributed data systems.

• Knowledge of AI/ML data requirements and concepts of feature engineering.

• Experience in industrial IoT or edge-to-cloud platforms.

• Familiarity with manufacturing systems and integration of OT and IT.

• Experience with cloud data platforms, with a preference for AWS.

• Understanding of streaming architectures.

• Familiarity with event-driven systems.

• Knowledge of data governance frameworks.

• Must be at least 18 years old.

• Successful completion of a drug test and background check is required.

• Authorization for periodic background checks as mandated by CFATS or relevant regulations.

🏝️ Benefits

• Access to tools, training, and opportunities for ongoing development.

• An inclusive culture that promotes growth, collaboration, and accountability.

• Opportunities for travel to manufacturing sites and partner locations as needed (~10–25%).