1. Job Purpose

The Lead Engineer, Operational Technology is responsible for building and operating the manufacturing data platform and IoT architecture, implementing MES and integrating it with ERP/SAP systems. This role acts as the Application Owner for plant digitalization systems, ensuring lifecycle management, system availability, and compliance. The position also ensures Computerized System Validation (CSV) and Data Integrity (DI) of all OT systems across manufacturing operations.

2. Key Responsibilities

1. Data Management & IoT Architecture Leadership

• Design and implement OT data architecture, End‑to‑End Level 3–4 data models, and ensure alignment with corporate data frameworks.
• Structure and govern manufacturing data (e.g., SAP data) to enable advanced analytics.
• Establish data governance policies including data quality, ownership, lifecycle management, retention, backup/restore, and auditing processes.
• Coordinate with Security teams for application‑layer hardening and compliance.

2. Manufacturing Operation Management Systems (MES, SAP…)

• Deploy, operate, and continuously optimize the MES system and integrate it with ERP/SAP.
• Develop and maintain Level 3–4 interfaces (API, event bus, OPC UA, MQTT) between MES and related systems.
• Perform OT system administration: incident handling, change control, request fulfillment, software monitoring, license renewal, security updates, and compliance.
• Serve as the local contact point for OT software and applications, bridging communication between business users and global IT/OT teams.
• Deliver user trainings and develop SOPs, guidelines, and work instructions.

3. Validation & Data Integrity Leadership

• Define, review documentation, perform testing and qualification of systems and applications across existing production equipment, OT infrastructure, facility, QC labs, R&D services, and the HD plant.
• Identify OT systems impacting product quality, Data Integrity (DI), and patient safety; develop OT system data flows and support risk assessments.
• Operate and maintain OT systems in accordance with CSV roadmap and validation requirements.
• Work with Quality Management to ensure documentation readiness (traceability, deviation/CAPA, periodic review) and maintain audit‑ready evidence.

4. OT Equipment Integration, Data Science, AI & Machine Learning Support

• Research and apply best practices in Manufacturing Analytics & Intelligence.
• Drive continuous improvement and innovation using data intelligence, applying advanced analytics for predictive and prescriptive insights.
• Review OT checklists, URS/FS for new equipment and automation projects.

3. Authorization

• Review OT designs from suppliers; approve URS/FS and design reviews.
• Approve acceptance tests and validation testing.
• Approve project reports and propose training programs.

4. Internal & External Relationships

Internal

• OpEx & Technology Manager: Direct reporting.
• System/Application Owners (Production, QC, Facility, etc.): Support in system administration and lifecycle activities.
• IT Engineers: Coordinate on OT–IT network, server, and platform connectivity.
• Quality Management (QM): Support CSV & DI activities, validation documentation.
• Project Leaders/Managers: Review and approve OT‑related technical documents.

External

• Global IT/OT & Smart Manufacturing Teams: OT asset documentation, knowledge sharing, system alignment.
• Suppliers: Ensure compliance in software, hardware, licensing, and security.
• B. Braun Technology Center / Global Project Teams: New equipment development and system integration.

5. Qualifications

Education

Must-have:

• Bachelor’s degree in Automation, Electronics & Communication, IT, Data/Business Analysis, or Data Science.

Nice-to-have:

• Understanding of ISA‑95, industrial data architectures (historians, time-series, event-driven systems).
• Knowledge of Data Integrity (ALCOA+), 21 CFR Part 11, EU Annex 11, GAMP 5.
• Certifications such as CCNA, MCSA; Azure Administrator.
• Knowledge of Windows Server & Linux.
• Scripting/programming skills: JavaScript, Python, VBA, SQL.

Experience

Must-have:

• 2–5 years in OT/MES/Data management in manufacturing (preferably medical devices, pharmaceuticals, food, or GxP environments).

Nice-to-have:

• Hands-on MES deployment integrated with ERP/SAP.
• Experience with OPC UA, MQTT, REST APIs.
• CSV/Validation experience (URS/FS/DS, IQ/OQ/PQ, change control, CAPA, traceability).
• Experience with software lifecycle management, SCADA, and industrial communication networks.

Skills

• Strong data sense, systematic thinking, and excellent analytical & problem-solving skills.
• Proficiency in office tools and data management platforms.
• Good English communication skills.
• Strong teamwork and interpersonal skills.
• Curious, flexible, open-minded; able to work independently with structure and commitment.