OT Data Engineer

Job Summary:

The OT Data Engineer will play a central role in building, scaling, and maintaining the data infrastructure that supports digital manufacturing, real‑time operations, and advanced analytics across our pharmaceutical production network. This role focuses on integrating shop‑floor systems, implementing a robust Unified Namespace (UNS) architecture, and leveraging HighByte Intelligence Hub to enable contextualized, reliable, and compliant data flows for manufacturing, quality, and business stakeholders.

Responsibilities

• Design, implement, and maintain a Unified Namespace (UNS) to standardize real‑time data access across OT, IT, and enterprise systems.

• Deploy and configure High Byte Intelligence Hub for data modeling, contextualization, transformation, and secure data movement between OT and cloud platforms.

• Integrate data from PLC/SCADA systems, historians (e.g., PI, IP.21), MES, LIMS, and IoT devices into the UNS and analytics platforms.

• Build and maintain data pipelines that support real‑time monitoring, predictive analytics, digital twins, and process optimization.

• Collaborate with automation, process engineering, quality, and IT teams to ensure 21 CFR Part 11, GxP, and data integrity compliance.

• Develop and maintain data models, ontologies, and asset hierarchies aligned with ISA‑95/ISA‑88 standards.

• Implement data governance, including metadata management, lineage tracking, and access control.

• Support advanced analytics and machine learning initiatives by ensuring high‑quality, contextualized data availability.

• Troubleshoot data flow issues across OT/IT boundaries and optimize system performance.

• Contribute to the roadmap for Industry 4.0, smart manufacturing, and digital transformation initiatives.

• Experience:

• Bachelor’s degree in engineering, Computer Science, Information Systems, or related field.

• 3–7 years of experience in OT data engineering, industrial data systems, or manufacturing IT.

• Hands‑on experience with:

• Unified Namespace (UNS) architectures

• HighByte Intelligence Hub (data modeling, flows, connectors)

• MQTT brokers (Ignition, HiveMQ, EMQX)

• Industrial protocols (OPC UA, Modbus, Ethernet/IP)

• Strong understanding of pharma manufacturing environments, including GxP, validation, and data integrity requirements.

• Proficiency in Python, SQL, and modern data engineering tools.

• Experience with cloud platforms (Azure, AWS, or GCP) and edge‑to‑cloud architectures.

• Experience with ISA‑95/ISA‑88 modeling and enterprise‑to‑shop‑floor integration.

• Knowledge of data analytics, statistical process control, or machine learning workflows.

• Experience with Ignition, Kepware, or similar industrial middleware.

• Familiarity with historians, MES, Tulip and automation systems.

Skills and Ability

• Strong problem‑solving and root‑cause analysis skills.

• Ability to translate manufacturing needs into scalable data solutions.

• Excellent communication skills for cross‑functional collaboration.

• Detail‑oriented mindset with a focus on reliability and compliance.

• Passion for digital transformation and modern OT/IT convergence