Greif

Greif

Process Engineer - Paper Mill

Baltimore-OH · Junior

Sponsorship not specified$82k-$139kDetected 30 days ago
Data AnalysisData VisualizationExcelProcess ImprovementCustomer SupportMechanical DesignControlsWordPressCommunicationProblem Solving

About the role

  • This role works closely with Operations and reports to the Technical Manager while partnering daily with production, maintenance, and reliability teams.
  • Monitor daily process performance across assigned areas (e.g., stock prep, wet end, dry end, utilities) and identify gaps vs. targets

Responsibilities

  • Develop and maintain reports, dashboards, and data summaries to support decision-making
  • Utilize process data from distributed control systems (DCS) to troubleshoot issues and support process optimization
  • Support root cause analysis efforts and assist in implementing corrective actions
  • Partner with operations teams to improve runnability, reduce breaks, and stabilize processes
  • Develop and maintain process documentation, standard work, and operating guidelines
  • Support cost reduction efforts through improved fiber usage, chemical optimization, and energy efficiency
  • Participate in safety initiatives and ensure processes are designed and operated safely
  • Collaborate with maintenance and reliability teams to address equipment-related process issues
  • Provide technical support during upset conditions and help lead problem-solving activities on the floor
  • The company delivers trusted, innovative, and tailored solutions that support some of the world's most in demand and fastest-growing industries.

Requirements

  • If you have concerns about the legitimacy of a job posting, receive an unsolicited job offer or suspect fraudulent activity, please contact us for verification via this link Contact Us - Greif.
  • Bachelor's degree in Chemical Engineering, Mechanical Engineering, Paper Science, or a related engineering field.
  • Strong data analysis skills with advanced proficiency in Microsoft Excel (ability to work with large data sets, functions, and basic data visualization)
  • Ability to work collaboratively with cross-functional teams

Nice to have

  • Assist with grade changes, trials, and process optimization initiatives
  • Track and report key performance indicators (KPIs) such as production rate, waste, energy use, and quality metrics
  • Assist in commissioning, startup, and optimization of new equipment or process upgrades

Skills

  • Analyze process and production data using Excel or similar tools to identify trends, losses, and improvement opportunities
  • Strong problem-solving and analytical skills
  • Effective communication skills, both on the floor and in meetings

Compensation

  • The pay range for this position is $81,800.00 - $139,200.00 annually.
  • Typically, a competitive wage for new hires will fall between $101,000.00 to $105,000.00 annually.
  • The position may also be eligible for a short-term incentive.
  • We offer a competitive salary, excellent benefits and opportunity for growth.

Benefits

  • Greif offers a comprehensive benefits package, including medical, dental, paid time off, and other competitive benefits which are available for eligible colleagues effective day one.
  • Benefits Statement:
  • We will not discriminate against any applicant or employee on the basis of sex, race, religion, age, national origin, color, disability, veteran status or any other any other legally protected characteristic.

Company info

  • This is typically an entry-level role ideal for candidates with a strong technical foundation, strong data analysis capability, and interest in manufacturing and career advancement.

Equal opportunity

  • https://www.greif.com/wp-content/uploads/2023/04/HR-101-Equal-Employment-Opportunity-Policy-English.pdf
  • We offer a competitive salary, excellent benefits and opportunity for growth.
  • Greif is an equal opportunity employer.
  • For more information read Greif's Equal Opportunity Policy.

This listing is sourced directly from Greif's careers page and normalized into a canonical job model.