Process Engineer - Data Analytics

AFL

Duncan (SC)

On-site

USD 65,000 - 90,000

Full time

14 days+

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Benefits offered by this job

Flexible time off policy
401K Company match (up to 4%)
Professional development, training, &

Job summary

AFL, a leading manufacturer of fiber optic cable and connectivity, seeks a Manufacturing Data Analyst to build data-driven tools for production and engineering decisions. The role emphasizes high-volume, high-mix manufacturing data analysis and actionable insights to drive capacity and throughput improvements.

You will collaborate across production and engineering teams, update legacy processes, and develop KPIs to monitor performance and guide scheduling efforts in a fast-paced environment.

Qualifications

  • Requires data analytics capability with practical, actionable outcomes.
  • Proficiency in data analysis tools (Excel, SQL, Power BI) and manufacturing software.
  • Bachelor’s degree in a manufacturing-related engineering field.

Responsibilities

  • Build and maintain data-driven tools and reporting to support production decisions.
  • Analyze high-mix manufacturing data to identify bottlenecks, flow constraints, capacity issues, and improvements.
  • Provide forward-looking insights to help engineering stay ahead of demand shifts.
  • Improve production visibility and responsiveness in a changing environment.
  • Support process improvements, layout changes, and flow optimization.
  • Work cross-functionally with production, engineering, and leadership.
  • Update legacy manufacturing processes to support current market trends and increased production demands.
  • Observe operations, collect data, and build data streams to support standards and capacity understanding.
  • Develop tools to track performance and ensure long-term success.
  • Analyze actual vs realized capacity and close performance gaps.
  • Focus operations on KPIs to drive growth and continuous improvement.
  • Design, launch, and track meaningful manufacturing KPIs.
  • Train operations teams to manage performance using data.

Skills

Data analytics
Excel proficiency
Problem solving
Strong communication

Education

Bachelor’s degree in mechanical, industrial, or manufacturing engineering

Tools

Excel
SQL
Power BI
Python

Job description

AFL manufactures industry-leading fiber optic cable, connectivity and accessories and provides engineering and installation services for some of the largest telecom customers in the world. Our company was founded in 1984 with a single fiber optic cable and today, we manufacture thousands of products, generate an excess of $3B in revenue, and employ approximately 13,000 associates worldwide. At AFL, we recognize that our employees are our greatest asset. We hire and train each individual, investing in them to ensure success in their careers. With a commitment to professional development and growth, let us connect you to your next career opportunity.

What We Offer:
  • Flexible time off policy
  • 401K Company match (up to 4% - dollar for dollar)
  • Professional development, training, and tuition reimbursement programs
  • Excellent medical, dental, vision, and life insurance policy options
  • Opportunities for career advance with an industry leading company!
Responsibilities:
  • Build and maintain data-driven tools and reporting to support production and engineering decisions
  • Analyze high-mix manufacturing data to identify:
    • Bottlenecks
    • Flow constraints
    • Capacity issues
    • Improvement opportunities
  • Provide forward-looking insights to help engineering stay ahead of demand shifts
  • Improve production visibility and responsiveness in a constantly changing environment
  • Support process improvements, layout changes, and flow optimization
  • Work cross-functionally with production, engineering, and leadership
  • Update legacy manufacturing processes to support current market trends and increasing production demands.
  • Observe operations with a critical eye, collect trustworthy data, and build clean data streams to support process standards, corrections, new ground level scheduling efforts, operations capacity and loading understanding, and increase capacity.
  • Use engineering expertise, objective analysis, and professional judgment to improve, create, and sustain high performing processes capable of handling high mix.
  • Develop tools and systems to track performance and ensure immediate and long-term success.
  • Support new plantwide scheduling initiatives by developing tools and processes to properly load and synchronize operations.
  • Analyze actual vs. realized capacity and implement strategies to close performance gaps.
  • Focus operations on key performance indicators to drive measurable growth and continuous improvement.
  • Design, launch, and track meaningful manufacturing KPIs.
  • Train operations teams to understand and manage performance using data and metrics.
  • Actively contribute to a respectful, high-functioning team culture.
  • Build strong relationships across departments to foster collaboration and shared ownership.
  • Serve as a technical partner and mentor to peers and operations staff.
Qualifications:
  • Bachelor’s degree in mechanical, industrial, or manufacturing engineering (or related field).
  • 2-3 years of experience in high-volume manufacturing environments preferred.
  • Strong data analytics capability (core requirement); Proficiency in data analysis tools (Excel, SQL, Power BI, etc.) and manufacturing software.
  • Python experience preferred (data analysis, automation, or tool development)
  • Ability to operate effectively in a fast-changing, low-structure environment
  • Strong problem-solving skills with a focus on practical, actionable outcomes
  • Exceptional analytical and critical thinking skills.
  • Strong mechanical aptitude and understanding of machining principles.
  • Demonstrated ability to lead projects and drive change through influence and expertise.
  • Excellent communication and interpersonal skills.
  • Passion for teamwork, continuous improvement, and building a collaborative culture.
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