
Staff Engineer OT Digital Systems
The Hershey Company17 days ago
Hershey, PA, USAStaff+
Responsibilities
- Design, build, and maintain Unified Namespace architecture using MQTT-based technologies.
- Develop semantic data models and hierarchical structures aligned with ISA-95 and ISA-88.
- Integrate PLC/SCADA, historian, MES, WMS, production planning, QMS, and ERP systems.
- Implement and support HiveMQ, HighByte, Inductive Automation Ignition, and historian platforms such as AVEVA PI.
- Develop Python scripts, ETL jobs, API integrations, data pipelines, and automation.
- Establish OT data governance standards and enable real-time, event-driven data architectures.
- Collaborate across OT, IT, and Engineering to support Digital Factory and MES initiatives.
- Provide on-site manufacturing support as needed, including occasional off-hours support.
Requirements
- Bachelor’s degree in Engineering, Computer Science, or a related field.
- At least 5 years of industrial data engineering or OT experience.
- Experience with Unified Namespace and MQTT architectures and with HiveMQ, HighByte, or similar platforms.
- Experience with the Inductive Automation Ignition platform and integration of MES, ERP, and control systems.
- Proficiency in Python and pipeline orchestration and transformation tools.
- Knowledge of ISA-95, ISA-88, and data modeling, plus experience with OT data governance.
- Experience with factory-floor industrial manufacturing technologies including PLCs, SCADA, and robotics.
- Preferred qualifications include AVEVA PI or other historian experience, familiarity with analytics, machine learning, AI platforms, and Databricks, API and event-driven architecture experience, Apache Kafka experience, and understanding of OT cybersecurity.
Benefits
- The role is based in Hershey, Pennsylvania, or remote, with travel to manufacturing sites as needed.
- Occasional off-hours support is required.
- The Hershey Company is an Equal Opportunity Employer and provides reasonable accommodation for applicants with disabilities.
Tech Stack
Categories
Data Engineering