OT Data Engineer
Job Type : Contract
Duration : 6+ Months
Experience : 3-7 years
Job Description: OT Data Engineer
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.
Key Responsibilities
Design, implement, and maintain a Unified Namespace (UNS) to standardize real‑time data access across OT, IT, and enterprise systems.
Deploy and configure HighByte 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.
Required Qualifications
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.
Key Competencies
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
