Weekend Shift Production Supervisor

101 Bloom Energy; United States; On-site; USD 75,000 - 107,000; Full time

Job summary

Bloom Energy in Newark, DE is seeking a Manufacturing Supervisor for the weekend shift (Fri–Sun, 6 am–6 pm) on-site. You will supervise a manufacturing team, drive safety, quality and efficiency, and implement standardized work practices.

The role reports to the Manufacturing Manager and requires leadership across leads, operators, and support functions. Responsibilities include coordinating schedules, limiting downtime, and using data to pinpoint root causes of defects.

Qualifications

• 3+ years of supervisory experience in manufacturing/operations.
• Experience with production systems; scale-up and lean methods.
• Proficient in interviewing, training, and handling disciplinary matters.
• Strong data analysis and data-driven decision making.

Responsibilities

• Supervise and motivate a manufacturing team toward safety, quality and efficiency targets.
• Oversee team leads and resources to meet production schedules.
• Create, document, and sustain standardized work practices.
• Develop and implement production scalability and workflow plans.
• Lead problem solving to resolve issues affecting production.
• Prepare production reports and manage dashboards for decision making.

Skills

Supervisory experience

Production systems experience

MS Office

Data analysis

Communication skills

Problem solving

Planning & organization

Interpersonal skills

Disciplinary handling

Education

High School Diploma or equivalent

Associate or Bachelor’s Degree preferred

Tools

MS Office programs

Job description

Bloom Energy in Newark, DE is seeking a Manufacturing Supervisor for the weekend shift (Fri–Sun, 6 am–6 pm) on-site. You will supervise a manufacturing team, drive safety, quality and efficiency, and implement standardized work practices.

The role reports to the Manufacturing Manager and requires leadership across leads, operators, and support functions. Responsibilities include coordinating schedules, limiting downtime, and using data to pinpoint root causes of defects.