Manufacturing Systems Integration Engineer

Role Purpose

We are seeking a Manufacturing Systems Integration Engineer to design, implement, and maintain complex integrations across Operational Technology (OT) and Information Technology (IT) systems in a global manufacturing environment. This role requires technical expertise in industrial communication protocols, data pipelines, and system interoperability to ensure successful deployment of digital manufacturing solutions.

Key Responsibilities

• Design and implement system integrations between OT platforms and IT systems using OPC UA, AMQP-based message buses, REST APIs, SQL, and custom connectors.
• Develop and maintain Ignition SCADA integrations for real-time visualization and control.
• Configure and manage Kepware OPC servers for data acquisition from PLCs and field devices.
• Integrate MES (Siemens Opcenter, ZNT-PAC) with upstream/downstream systems for production execution and traceability.
• Enable reporting and visualization through SSRS and Power BI, including dashboards for OEE, SPC, and quality analytics.
• Collaborate with data engineering teams to integrate OT data into Databricks for advanced analytics and machine learning use cases.
• Execute integration projects from requirements gathering through deployment, ensuring within scope and on-time.
• Cook up change management activities, including communication plans, training, and user adoption strategies.
• Act as a technical advisor and change champion, ensuring smooth transition to new systems and processes.

Required Qualifications

• Bachelor’s degree in Engineering, Computer Science, or related field.
• 3+ years of experience in manufacturing systems integration or OT/IT convergence.
• Strong hands-on experience with:
• Ignition SCADA configuration and scripting (Python/Java-based).
• OPC/UA and Kepware for industrial connectivity.
• MES platforms (Siemens Opcenter, ZNT-PAC) integration.
• Software development experience in Python, Java, or .NET for custom integrations.

Desired Qualifications

• Familiarity with cloud analytics platforms (Databricks, Azure, AWS) and data lake architectures.
• Experience with containerization (Docker) and orchestration (Kubernetes) for deployment.
• Exposure to machine learning workflows using manufacturing data.
• Experience with change management frameworks is a plus.

Working Conditions

• Travel to manufacturing sites (domestic/international) for discovery, deployment, and support.
• Flexibility to support cutovers, validations, or critical events outside standard hours.