Plant Data Engineer

Key Responsibilities:

Manufacturing:

• Identify and implement Industry 4.0 concepts, such as IoT (Internet of Things), AI (Artificial Intelligence), machine learning, and predictive maintenance, to monitor and control plant operations in real-time

• Collaborate with departments to explore, identify, and utilize digital technologies, data analytics and automation systems to integrate digital tools with existing production processes and systems, transforming our manufacturing site

• Collect, analyze, and interpret operational data using advanced data analytics tools and platforms to make data-driven decisions and drive continuous improvement initiatives

• Develop and manage dashboards and reporting systems for real-time monitoring of key performance metrics, equipment performance, and product quality

Environment, Health & Safety (EHS):

• Support the EHS department by analysing safety data to help improve the plant's EHS standards

• Ensure production processes are conducted in compliance with EHS standards and statutory regulations

• Assist lead in troubleshooting during emergencies and be part of the emergency management team

• Act as the plant representative to provide operational concerns on Management of Change (MOC) processes, ensure they are safely evaluated and do not introduce new hazards

Plant Performance:

• Address and resolve technical issues in the production process promptly to ensure minimal downtime, operating on a 24/7 basis

• Prepare and present Overall Equipment Efficiency (OEE) reports using data analytics tools and identify improvement opportunities

Maintenance and Shutdown/Overhaul Activities:

• Assist lead in predictive maintenance programs by using sensor data, machine learning, and AI tools to predict equipment failures and reduce downtime

• Collaborate with the maintenance department to support the effective deployment of predictive maintenance technologies

• Support plant overhaul and lead the documentation of shutdown/startup operational findings and suggest improvements

People & Competency Management/Development:

• Provide training to production technicians, shift supervisors, and production day staff on the use of new digital tools and systems.

• Stay up to date with the latest Industry 4.0 technologies and innovations, ensuring that the plant remains at the forefront of digital transformation.

• Provide input to Operation Event Reporting (OER), maximizing learning and awareness, improving knowledge and skills of the shift team, thereby reducing recurrence of similar events.

• Work with the training specialist to assess the effectiveness of training systems through the use of data.

Continuous Improvement:

• Drive the adoption of best practices in the areas of digitalization, automation, and process optimization.

• Apply continuous improvement methodologies to identify inefficiencies and recommend solutions.

• Assess the latest technological advancements in automation, digitalization, Industry 4.0 technologies, and sustainable practices, and implement relevant technologies to operational processes.

Other Expectations:

• Participate in audits and other activities as assigned to ensure compliance with EHS, PSM (Process Safety Management), and manufacturing standards, as well as to maintain updated operational systems.

• Work with operations shift supervisors, training specialists, and stakeholders from other departments to achieve the accountabilities above.

• Perform other duties as assigned to meet business and operational needs, e.g., part of the Emergency Response Organization (ERO).

Qualifications:

• Degree in Process or Chemical Engineering from a recognized tertiary institution with electives in Data Engineering

• Minimum 3 years of experience in production engineering or in operating a high hazard chemical plant would be advantageous

• Experience in operational emergency management in a high hazard chemical plant is preferred

• Hands-on experience with data engineering tasks and projects

• Understanding in data-driven decision making, and other automation and manufacturing tools

• Knowledge in data engineering

• Excellent written and spoken English skills