What are the responsibilities and job description for the Process Control Engineer position at PTS Advance?
Process Control Engineer β Refinery (Contract) | Big Spring, TX
Overview
We are seeking experienced Process Control Engineers to support refinery operations in Big Spring, TX. This role will focus on providing hands-on control system support, optimizing unit performance, and ensuring safe, reliable operation across key refinery processes.
The ideal candidate brings strong refinery experience and can quickly contribute to both day-to-day operations and troubleshooting efforts.
Key Responsibilities
- Provide process control support for refinery units, ensuring stable and efficient operations
- Monitor and troubleshoot control systems, including loop tuning and performance optimization
- Partner with operations and engineering teams to resolve process upsets and operational issues
- Review and improve control strategies to align with current plant conditions and production goals
- Support root cause analysis and implement corrective actions for recurring issues
- Perform field verification activities such as instrumentation checks, loop validation, and system walkdowns
- Assist with unit optimization and continuous improvement initiatives
Unit Experience (Preferred)
- Hydrotreating
- Reforming
- Utilities systems, including:
- Boilers
- Boiler Feed Water (BFW) systems
- Wastewater treatment
Qualifications
- 5 years of refinery experience preferred (process control or process engineering background)
- Hands-on experience with process control systems in a refining environment
- Strong understanding of process dynamics, control strategies, and unit operations
- Proven ability to troubleshoot and solve moderately complex operational problems
- Comfortable working in both field and control room environments
- Strong communication and teamwork skills
Work Environment & Schedule
- Onsite role in Big Spring, TX
- Combination of control room support and field-based activities
- Standard refinery work schedule, with flexibility based on operational needs