Data Initiatives Engineer – AI for Equipment Reliability

Energy Transfer; Houston (TX); On-site; USD 85,000 - 120,000; Full time

Job summary

Energy Transfer is seeking an Engineer to join the Data Initiatives Group in Houston, supporting data-driven innovation and the integration of emerging technologies into Operations.

You will help develop an in-house rotating equipment failure prevention and predictive maintenance program, including data collection, ML modeling, data interpretation, and equipment monitoring, coordinating with Operations teams to diagnose anomalies and maintain uptime.

Qualifications

• Bachelor’s degree in Engineering discipline.
• 0-3+ years’ experience in Oil and Gas Industry.
• Must possess strong troubleshooting, problem solving, communication, and interpersonal skills.

Responsibilities

• Support Data Initiatives Group with data enhancement and standardization for field operations.
• Build, train, and provide ongoing support for ML models focused on reliability and optimization.
• Monitor models for equipment anomalies and coordinate with field personnel to maintain equipment.
• Enter and import raw equipment data into a standardized data system.
• Assist with creation of AI-centric programs to optimize maintenance and reliability.
• Provide day-to-day engineering and technical support for data initiatives.
• Identify and develop scopes for future data enhancement projects.
• Collaborate with Operations Stakeholders to oversee equipment reliability and uptime.

Skills

Troubleshooting

Communication

Interpersonal skills

Time management

Education

Bachelor’s degree in Engineering

Job description

Energy Transfer is seeking an Engineer to join the Data Initiatives Group in Houston, supporting data-driven innovation and the integration of emerging technologies into Operations.

You will help develop an in-house rotating equipment failure prevention and predictive maintenance program, including data collection, ML modeling, data interpretation, and equipment monitoring, coordinating with Operations teams to diagnose anomalies and maintain uptime.