What are the responsibilities and job description for the Industrial UNS Data Modeller position at Vibotek LLC?
Role Title: Industrial UNS Data Modeller
City: Georgetown
State: KY
Mandatory Skills: Functional experience in manufacturing operations Experience with data modelling in industrial settings Familiarity with manufacturing data integration across MES, SCADA, ERP
Role Description Skills
Job Title: Manufacturing Unified Namespace (UNS) Data Modeler Position Summary We are looking for an experienced Unified Namespace (UNS) Data Modeler to design, structure, and maintain data models that support real-time, contextualized data flow within our enterprise-wide UNS architecture. In this role, you will define how industrial data is represented, named, and organized to enable seamless integration across OT and IT systems and support analytics, automation, and decision-making. You will work at the intersection of operations, data engineering, and industrial automation to ensure that data from machines, processes, and systems is structured semantically and consistently across the enterprise.
Key Responsibilities
Data Modeling & Taxonomy Development Develop and maintain logical and physical data models for the UNS, including hierarchical topic structures, metadata schemas, and contextual relationships.
Apply ISA-95 and ISA-88 standards to define consistent information models across equipment, processes, and enterprise functions.
Model real-time data using Sparkplug B or similar protocols for semantic interoperability.
Namespace Governance Define and enforce naming conventions, tag standards, and data object hierarchies within the UNS.
Collaborate with teams to manage changes to data models and ensure alignment with organizational data governance policies.
Cross-Functional Collaboration Work with automation engineers, IT, data scientists, and business analysts to translate operational needs into semantic models.
Act as the subject matter expert for contextual data structuring in MQTT-based architectures.
Quality & Optimization Ensure data integrity, consistency, and completeness across all layers of the namespace.
Recommend improvements to namespace performance, usability, and scalability.
Documentation & Communication Maintain comprehensive documentation of models, metadata, and semantic structures.
Provide training and support to teams consuming data from the UNS.
Required Qualifications
Bachelor’s degree in Data Science, Engineering, Computer Science, or related field.
3 years of experience in data modeling, preferably in an industrial, manufacturing, or IIoT environment.
Functional experience with manufacturing operations: Production, Internal Logistics, Quality Assurance, Maintenance Strong understanding of industrial data standards (ISA-95, ISA-88), MQTT, Sparkplug B, and OPC UA.
Familiarity with data integration across SCADA, MES, ERP, and cloud systems.
Proficient in using data modeling tools (e.g., ER/Studio, Lucidchart, or enterprise architecture platforms).
Strong analytical, communication, and documentation skills.
Preferred Qualifications Experience designing or working with Unified Namespace architectures.
Knowledge of asset modeling frameworks like AAS, Digital Twin, or OPC UA Companion Specs.
Experience with time-series databases, event streaming platforms, or data lakes.
Exposure to manufacturing environments or industry 4.0 projects.
City: Georgetown
State: KY
Mandatory Skills: Functional experience in manufacturing operations Experience with data modelling in industrial settings Familiarity with manufacturing data integration across MES, SCADA, ERP
Role Description Skills
Job Title: Manufacturing Unified Namespace (UNS) Data Modeler Position Summary We are looking for an experienced Unified Namespace (UNS) Data Modeler to design, structure, and maintain data models that support real-time, contextualized data flow within our enterprise-wide UNS architecture. In this role, you will define how industrial data is represented, named, and organized to enable seamless integration across OT and IT systems and support analytics, automation, and decision-making. You will work at the intersection of operations, data engineering, and industrial automation to ensure that data from machines, processes, and systems is structured semantically and consistently across the enterprise.
Key Responsibilities
Data Modeling & Taxonomy Development Develop and maintain logical and physical data models for the UNS, including hierarchical topic structures, metadata schemas, and contextual relationships.
Apply ISA-95 and ISA-88 standards to define consistent information models across equipment, processes, and enterprise functions.
Model real-time data using Sparkplug B or similar protocols for semantic interoperability.
Namespace Governance Define and enforce naming conventions, tag standards, and data object hierarchies within the UNS.
Collaborate with teams to manage changes to data models and ensure alignment with organizational data governance policies.
Cross-Functional Collaboration Work with automation engineers, IT, data scientists, and business analysts to translate operational needs into semantic models.
Act as the subject matter expert for contextual data structuring in MQTT-based architectures.
Quality & Optimization Ensure data integrity, consistency, and completeness across all layers of the namespace.
Recommend improvements to namespace performance, usability, and scalability.
Documentation & Communication Maintain comprehensive documentation of models, metadata, and semantic structures.
Provide training and support to teams consuming data from the UNS.
Required Qualifications
Bachelor’s degree in Data Science, Engineering, Computer Science, or related field.
3 years of experience in data modeling, preferably in an industrial, manufacturing, or IIoT environment.
Functional experience with manufacturing operations: Production, Internal Logistics, Quality Assurance, Maintenance Strong understanding of industrial data standards (ISA-95, ISA-88), MQTT, Sparkplug B, and OPC UA.
Familiarity with data integration across SCADA, MES, ERP, and cloud systems.
Proficient in using data modeling tools (e.g., ER/Studio, Lucidchart, or enterprise architecture platforms).
Strong analytical, communication, and documentation skills.
Preferred Qualifications Experience designing or working with Unified Namespace architectures.
Knowledge of asset modeling frameworks like AAS, Digital Twin, or OPC UA Companion Specs.
Experience with time-series databases, event streaming platforms, or data lakes.
Exposure to manufacturing environments or industry 4.0 projects.
