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Key Responsibilities and Required Skills for Digital Manufacturing Engineer

💰 $ - $

EngineeringManufacturingDigital TransformationIndustry 4.0

🎯 Role Definition

A Digital Manufacturing Engineer designs, implements and scales digital systems and automation solutions that connect plant-floor operations with enterprise systems to improve throughput, quality, flexibility and cost. This role leads the specification, deployment and continuous improvement of MES/MOM, IIoT solutions, Digital Twins, process automation (PLC/robotics), data integration, and analytics to enable smart manufacturing and Industry 4.0 initiatives.

Key target outcomes: reduced cycle time, improved first-pass yield, real-time production visibility, predictive maintenance, standardized digital work instructions, and measurable OEE uplift across lines and sites.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Manufacturing Engineer (Process/Production)
  • Controls / Automation Engineer
  • Industrial Engineer

Advancement To:

  • Senior Digital Manufacturing Engineer / Lead Engineer
  • Digital Transformation Manager / Industry 4.0 Program Manager
  • Manufacturing Engineering Manager / Plant Engineering Director

Lateral Moves:

  • MES/MOM Specialist or Architect
  • Automation / Controls Engineering Lead
  • Systems Integration Engineer

Core Responsibilities

Primary Functions

  • Lead the end-to-end design, specification, and deployment of Manufacturing Execution Systems (MES/MOM), including defining business processes, functional requirements, workflows, and KPIs to ensure MES integrates seamlessly with ERP, PLM, and control systems.
  • Architect and implement IIoT solutions and OT-IT integrations (OPC UA, MQTT, REST APIs) to capture real-time equipment data, enable edge analytics, and feed centralized analytics platforms for production visibility and decision support.
  • Develop and maintain Digital Twin and simulation models of production lines to validate layout changes, throughput scenarios, bottleneck mitigation, and to support virtual commissioning prior to physical changes.
  • Collaborate with PLC/controls, robotics, and automation teams to specify interface requirements, implement standardized data models, and deliver deterministic data feeds for analytics and MES workflows.
  • Drive programs to standardize electronic work instructions, checklists, and paperless operator interfaces using HMI/SCADA and mobile UI frameworks to reduce variation and improve operator compliance and training.
  • Design and implement predictive maintenance strategies leveraging machine condition data, vibration/temperature sensors, and analytics models to reduce unplanned downtime and extend mean time between failures (MTBF).
  • Lead proof-of-concept and pilot projects for new digital manufacturing technologies (vision systems, machine learning models, AR-enabled work instructions, additive manufacturing workflows) and shepherd successful pilots to scaled production deployments.
  • Define and implement OT cybersecurity best practices for manufacturing systems, including network segmentation, secure remote access, patching strategies, and coordination with corporate security teams to protect critical production assets.
  • Build and maintain data pipelines for manufacturing data lakes/warehouses, ensuring data quality, timestamp synchronization, schema management and lineage for accurate analytics and reporting.
  • Partner with quality engineering and R&D to implement in-line inspection, automated defect detection, and closed-loop quality control that reduces scrap and rework through real-time corrective actions.
  • Implement continuous improvement initiatives (Lean, Six Sigma) tied to digital metrics—translate process improvement opportunities into digital requirements and quantify impact through A/B testing and controlled rollouts.
  • Configure and maintain process parameter libraries, BOM/route synchronization with PLM/ERP, and enforce version control for software, recipes and digital work content to ensure consistent production behavior across shifts and sites.
  • Create and maintain technical documentation, control narratives, and test plans for digital systems; lead factory acceptance tests (FAT), site acceptance tests (SAT) and supervise commissioning and start-up activities.
  • Coach and upskill operators and engineers on new digital tools and data-driven ways of working; create training plans, e-learning modules and hands-on workshops to accelerate adoption.
  • Manage vendor relationships and evaluate third-party MES, SCADA, analytics platforms, and system integrators—drive procurement specifications, RFP evaluations and vendor performance KPIs.
  • Implement and monitor production KPIs (OEE, availability, performance, quality) in dashboards and scorecards that provide role-based visibility from operators to executives.
  • Troubleshoot production interruptions with cross-functional teams, perform root-cause analysis on digital and physical causes, and implement corrective actions that prevent recurrence.
  • Translate strategic digital manufacturing roadmaps into pragmatic project plans, resourcing, and budgets; track benefits realization and produce ROI analyses for leadership.
  • Ensure regulatory compliance and traceability for serialized products—implement digital batch records, genealogy, and e-signature workflows to satisfy audits and product safety requirements.
  • Lead cross-site rollouts of best-practice digital templates and reusable software artifacts to accelerate deployment across multiple plants with minimum disruption.
  • Monitor new developments in automation hardware, cloud-edge architectures, industrial AI and ML, and advise on technology adoption strategies that align with manufacturing roadmaps.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Maintain and update digital project risk registers; escalate blockers and recommend mitigation plans to stakeholders.
  • Assist procurement and finance with TCO, licensing, and maintenance estimates for digital manufacturing platforms.
  • Provide after-hours on-call support for critical manufacturing system incidents and partner with IT/OT for rapid resolution.
  • Review and approve change requests for software, PLC logic and production recipes to maintain a controlled change environment.

Required Skills & Competencies

Hard Skills (Technical)

  • Manufacturing Execution Systems (MES/MOM): specification, configuration, integration and lifecycle management (examples: Siemens Opcenter, Rockwell FactoryTalk, AVEVA, Dassault DELMIA).
  • OT-IT Integration: OPC UA, MQTT, RESTful APIs, MTConnect, and experience integrating MES with ERP (SAP/Oracle), PLM and SCADA systems.
  • PLCs and Controls: programming and troubleshooting experience with Allen-Bradley, Siemens S7, Schneider, and familiarity with ladder logic, structured text and motion control.
  • SCADA / HMI: design, screen development, alarming, historian configuration (e.g., Wonderware, Ignition, GE Proficy).
  • Industrial Networking & Cybersecurity: VLANs, firewall segmentation, secure VPN, NERC/ISA/IEC 62443 understanding for OT environments.
  • Data Engineering & Analytics: SQL, time-series data handling, ETL concepts, experience with data lakes/warehouses, and tools such as InfluxDB, Prometheus, or cloud services (AWS/Azure/GCP).
  • Programming / Scripting: Python, C#, Java, or node.js for automation, data ingestion, ETL scripting and analytics prototype development.
  • Digital Twin & Simulation tools: Factory simulation (AnyLogic, Simul8), CAD/CAM integration, and virtual commissioning tools.
  • Industrial AI/ML: experience applying predictive models for downtime, quality defects, or anomaly detection with frameworks like TensorFlow or scikit-learn.
  • Robotics & Motion Systems: integration with robotic cells, vision systems, and familiarity with ROS or robot vendor controllers.
  • Version control and CI/CD for industrial software: Git, artifact management, automated deployment practices for edge and cloud components.
  • Additive/Subtractive Manufacturing knowledge: process parameterization, CNC integration, post-processing traceability (when applicable).
  • Standards & Compliance: knowledge of ISO, GMP, FDA 21 CFR Part 11 (for regulated industries), and traceability/serialization requirements.

(At least 10 of the above should appear; tailor to the specific hiring context.)

Soft Skills

  • Strong stakeholder management and the ability to translate business problems into technical requirements and measurable outcomes.
  • Clear written and verbal communication; experience producing executive dashboards, technical specs, and training materials.
  • Cross-functional collaboration across manufacturing operations, IT, quality, safety, and supply chain teams.
  • Analytical and structured problem-solving with demonstrated root-cause analysis skills and data-driven decision making.
  • Project management and prioritization; experience running digital projects using Agile or hybrid delivery models.
  • Change management and coaching skills to drive adoption of new digital tools and processes.
  • Attention to detail, documentation discipline, and a bias for measurable results and continuous improvement.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Mechanical, Electrical, Industrial, Manufacturing, Systems Engineering, Computer Science, or related technical field.

Preferred Education:

  • Master's degree in Manufacturing Systems, Industrial Engineering, Controls & Automation, Data Science, or MBA with digital transformation emphasis.

Relevant Fields of Study:

  • Mechanical Engineering
  • Electrical / Controls Engineering
  • Industrial / Manufacturing Engineering
  • Computer Science / Software Engineering
  • Data Science / Applied Analytics

Experience Requirements

Typical Experience Range: 3–8 years in manufacturing/industrial settings, with hands-on experience in automation, MES, controls or data integration.

Preferred:

  • 5+ years specifically delivering digital manufacturing solutions, MES deployments, or IIoT/automation projects.
  • Prior experience working in regulated industries (pharmaceuticals, medical devices, food & beverage) or high-volume discrete manufacturing is highly desirable.
  • Certifications such as Six Sigma (Green/Black Belt), PMP/Agile, ISA/IEC security, Rockwell/Siemens certifications or vendor-specific MES certifications are a plus.
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