Role Summary

The Manufacturing Systems Engineer supports lifecycle management, maintenance, and optimization of PI Data Historian systems and modern data collection platforms across the manufacturing network. Working under the guidance of senior engineers, this role collaborates with cross-functional teams to ensure reliable data acquisition, integration, and analytics for manufacturing operations. The engineer contributes to digital transformation initiatives and operational excellence, with a focus on emerging data technologies. This role offers opportunities for professional development, mentorship, and growth within the PI COE and broader organization.

Key Responsibilities

• Support lifecycle upgrades, migrations, and enhancements of PI Data Historian systems across the Amgen network.

• Assist with PI scope for capital projects, ensuring adherence to technical and business standards.

• Support enterprise PI infrastructure, ensuring system reliability, performance, and compliance.

• Create scripts and tools to help manage PI systems across the network.

• Collaborate with global manufacturing, automation, and IT teams to implement PI solutions for data acquisition, integration, and reporting.

• Help maintain documentation, standards, and best practices for PI system architecture, security, and data governance.

• Assist in developing PI Asset Framework templates, Analyses, and PI Vision displays to meet business requirements.

• Troubleshoot and resolve routine PI system issues, escalating complex problems to senior engineers.

• Contribute to continuous improvement initiatives using PI data for process optimization and analytics.

• Participate in global PI COE activities, knowledge sharing, and training for site teams.

• Support compliance with regulatory requirements and quality standards in PI system activities.

• Assist with audits, validation, and change management processes related to PI systems.

Basic Qualifications

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

• 5+ years of experience in manufacturing systems engineering or industrial data platforms.

• Exposure to PI System lifecycle management, upgrades, and enterprise deployments.

• Familiarity with modern data collection technologies: UNS, MQTT, Kafka.

• Exposure to PI System components and technologies such as Data Archive, Asset Framework, PI Vision, PI Analyses/Notifications, and WebAPI.

• Familiarity with PI interface/Connector technologies including OPC UA/DA, PItoPI, BACNet, RDBMS, and UFL.

• Ability to develop scripts and tools in Python, PowerShell, and front-end frameworks (Angular, React).

• Exposure to batch interfaces such as EMDVB, FTBatch, and EFGen is a plus.

• Understanding of automation systems (PLC, SCADA) and data analytics concepts.

Preferred Qualifications

• Experience in pharmaceutical or regulated manufacturing environments.

• Knowledge of integration with MES and analytics platforms.

• Strong problem-solving and communication skills.

• Experience working in distributed teams and supporting multiple manufacturing sites.

• Certifications in PI System administration or related technologies are a plus.

• Experience with HighByte, HiveMQ or similar platform is a plus.

Work Environment

Onsite or hybrid, with collaboration across global time zones. Participation in PI COE meetings, lifecycle planning, and upgrade events; occasional extended hours for global coordination.