Senior Process Engineer — EDX & Digitalization
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Key skills for this role
About the Role
Yokogawa is seeking a Senior Process Engineer for its EDX & Digitalisation team in Abu Dhabi. The role involves leading process engineering deliverables for OTS, APC/MPC, digital twin, and data-driven optimisation projects.
Key Skills for This Role
Responsibilities
- Lead process engineering deliverables across the full EDX project lifecycle — OTS, APC/MPC, digital twin, and data driven optimisation
- Develop and validate high fidelity dynamic and steady state simulation models using Petro SIM, OmegaLand
- Design OTS training scenarios — normal operations, start up, shutdown, emergency response, and process upsets
- Apply deep knowledge of O&G and Refinery unit operations to develop engineering basis documents, interpret PFDs/P&IDs/H&MBs
- Support APC/MPC and optimisation project delivery: CV/MV/DV definition, operating constraint limits, step test planning
- Liaise with client DCS teams to ensure simulation compatibility with DCS replica architecture
- Contribute process domain knowledge to IT OT convergence and digital twin initiatives
- Represent the company at client kick off meetings, technical design reviews, and FAT/SAT milestones
Requirements
- Bachelor’s degree in Chemical Engineering or Process Engineering
- 7 to 12 years of professional experience in process engineering
- Proven hands on experience with dynamic and/or steady state process simulation tools (HYSYS Dynamics, Petro SIM, OmegaLand, DYNSIM, Aspen Plus, or equivalent)
- Direct experience with OTS development, model validation, or simulation based training projects
- Strong working knowledge of Oil & Gas and/or Refinery process operations and unit operations
- Solid understanding of process dynamics and their relationship to control system design and simulation behaviour
- Effective client facing communication skills in English
Full Job Posting
About the Role
- As a Process Engineer within the EDX & Digitalisation team, you will be the process domain authority on client projects — applying deep O&G and Refinery process knowledge to simulation development, control optimisation, and digital transformation engagements.
Key Responsibilities
- Lead process engineering deliverables across the full EDX project lifecycle — OTS, APC/MPC, digital twin, and data driven optimisation — from scope definition and data collection through model development, validation, and client sign off.
- Develop and validate high fidelity dynamic and steady state simulation models using Petro SIM, OmegaLand ; build OTS environments integrating process models with DCS replicas (Yokogawa, Honeywell, Emerson, or equivalent).
- Design OTS training scenarios — normal operations, start up, shutdown, emergency response, and process upsets — and develop supporting malfunction libraries, instructor guides, and trainee assessment frameworks.
- Apply deep knowledge of O&G and Refinery unit operations (separation, compression, distillation, treating, dehydration, and utilities) to develop engineering basis documents, interpret PFDs/P&IDs/H&MBs..
- Demonstrate applied understanding of process dynamics — dead time, lag, gain, interaction effects — translating dynamic process behaviour into OTS scenario parameters, APC model requirements, and controller tuning inputs.
- Support APC/MPC and optimisation project delivery: CV/MV/DV definition, operating constraint limits, step test planning, process response interpretation, and identification of optimisation opportunities across energy, yield, and throughput.
- Liaise with client DCS teams to ensure simulation compatibility with DCS replica architecture; support I/O mapping, interlock verification, and FAT/SAT activities.
- Contribute process domain knowledge to IT OT convergence and digital twin initiatives — informing data architecture, OT connectivity design, and historian integration strategies to support the broader DX programme.
- Apply awareness of AI/ML concepts — soft sensors, anomaly detection, predictive maintenance, and data driven optimisation — to contextualise AI outputs within a process engineering framework and support model validation.
- Represent the company at client kick off meetings, technical design reviews, and FAT/SAT milestones; maintain strong working relationships with client discipline engineers across process, instrumentation, DCS, and operations.
Qualifications & Experience
- Bachelor’s degree in Chemical Engineering or Process Engineering from a recognised university.
- 7 to 12 years of professional experience in process engineering, with a track record in process simulation and/or project delivery.
- Proven hands on experience with dynamic and/or steady state process simulation tools (HYSYS Dynamics, Petro SIM, OmegaLand, DYNSIM, Aspen Plus, or equivalent).
- Direct experience with OTS development, model validation, or simulation based training projects.
- Strong working knowledge of Oil & Gas and/or Refinery process operations and unit operations.
- Solid understanding of process dynamics and their relationship to control system design and simulation behaviour.
- Demonstrated ability to deliver technical work to schedule and quality in a project environment.
- Effective client facing communication skills — written and verbal — in English.
Preferred / Advantageous
- Prior experience working within a global automation OEM, major EPC contractor, or specialist engineering consultancy in a project delivery capacity.
- UAE or GCC regional experience — familiarity with local O&G operators, project execution norms, and client protocols.
- Practical plant operations or commissioning experience at an O&G or Refinery facility.
- Working knowledge of DCS systems deployed in UAE O&G facilities (Yokogawa, Honeywell, Emerson, ABB, or equivalent).
- Exposure to APC/MPC project delivery — step testing, model identification, controller commissioning, or performance monitoring.
- Awareness or hands on experience with AI/ML applications in process industries — soft sensors, predictive analytics, anomaly detection, or data driven optimisation.
- Familiarity with industrial IoT, cloud platforms (AWS, Azure, or equivalent), or data analytics tools used in OT environments.
- Familiarity with process data historians (OSIsoft PI, Yokogawa Exaquantum, AspenWatch) for model validation and performance analysis.
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