Lean Manufacturing Engineer

Siemens

Fort Worth (TX)

On-site

USD 85,000 - 120,000

Full time

2 days ago
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Job summary

Siemens is seeking a Lean Manufacturing Engineer for its Fort Worth, TX plant. You will lead data-driven process improvements, apply Lean methods, and collaborate with production teams to strengthen capacity and productivity in electrical products manufacturing.

The role focuses on throughput, productivity, and cost objectives, with opportunities to advance technical capabilities and deliver measurable results in a dynamic manufacturing environment.

Qualifications

  • Bachelor’s degree in Industrial Engineering or related field; combination with related experience considered.
  • At least 2 years of industrial/manufacturing engineering or continuous improvement experience in a manufacturing environment.
  • Experience contributing to manufacturing improvement projects impacting throughput, productivity, or cost.
  • Experience conducting time studies, analyzing labor requirements and capacity, identifying improvement opportunities.
  • Lean manufacturing methods experience: Kaizen, value stream mapping, standard work, waste elimination.
  • Strong analytical and problem-solving skills with data-driven recommendations.
  • Proficiency with Microsoft Excel and data analysis tools.
  • Strong communication and collaboration with production and cross-functional teams.
  • Legal authorization to work in the United States.

Responsibilities

  • Execute manufacturing improvement projects from analysis through implementation and follow-up.
  • Improve throughput by balancing lines and updating capacity models and workflows.
  • Apply Lean methods via Kaizen events, value stream mapping, standard work, and waste elimination.
  • Improve labor productivity and reduce operating costs through time studies and labor standards.
  • Support FPY improvements via root cause analysis, standardization, and error-proofing.
  • Maintain Daily Management Systems with dashboards to track KPIs and actions.
  • Partner with Operations, Quality, Logistics, Maintenance, and Supply Chain to document best practices and drive readiness.

Skills

Analytical thinking
Problem solving
Communication skills
Time study
Data analysis

Education

Bachelor’s degree in Industrial Engineering or related field

Tools

Microsoft Excel
Power BI
Minitab

Job description

Job Family: Electrical Products

Req ID: 528411

Here at Siemens, we take pride in enabling sustainable
progress through technology. We do this through empowering customers by
combining the real and digital worlds. Improving how we live, work, and move
today and for the next generation! We know that the only way a business thrive
is if our people are thriving. That’s why we always put our people first. Our
global, diverse team would be happy to support you and challenge you to grow in
new ways. Who knows where our shared journey will take you?

Transform the everyday with us!

Put your engineering expertise to work solving production
challenges and improving how electrical infrastructure is built. As a Lean Manufacturing Engineer with Siemens Smart Infrastructure’s Electrical Products
(EP) business, you’ll apply data analysis, Lean manufacturing methods, and
practical problem-solving to strengthen capacity, quality, and productivity.
You’ll own defined process improvement projects and collaborate with
experienced engineers and production teams on broader operational excellence
initiatives, building your technical capabilities while delivering measurable
results. Your work will support reliable production of electrical products that
empower customers and advance intelligent power distribution. This position is
based in our manufacturing plant in Fort Worth, Texas.

You will make an impact by:
  • Executingdefined manufacturing improvement projects from analysis throughimplementation and follow-up, coordinating milestones with stakeholdersand tracking results against throughput, productivity, and costobjectives.
  • Improvingproduction throughput by analyzing bottlenecks, balancing assembly lines,and updating capacity models and workflows to support output and deliverytargets.
  • ApplyingLean manufacturing methods through Kaizen events, value stream mapping,workplace organization, and standard work, collaborating with productionteams to eliminate waste and sustain improvements.
  • Improvinglabor productivity and reducing operating costs by conducting timestudies, developing and maintaining labor standards, and recommendingprocess changes supported by measurable efficiency gains.
  • Supportingfirst pass yield (FPY) improvements by partnering with Quality andOperations on root cause analysis, process standardization, anderror-proofing to reduce defects, scrap, and rework.
  • MaintainingDaily Management Systems (DMS) through OpsEdge, visual controls, andstructured problem-solving routines, using Microsoft Excel andmanufacturing dashboards to track key performance indicators (KPIs),identify trends, and support corrective actions.
  • Partneringwith Operations, Quality, Logistics, Maintenance, and Supply Chain todocument manufacturing best practices, support production readiness, trainemployees on updated standard work, and implement ergonomic and safetyimprovements.
You’ll win us over by having the following qualifications:
Basic Qualifications:
  • Bachelor’sdegree in Industrial Engineering, Manufacturing Engineering, MechanicalEngineering, Operations Management, or a related technical field. Acombination of education and directly related work experience will also beconsidered in lieu of a degree.
  • Atleast 2 years of relevant industrial engineering, manufacturingengineering, or continuous improvement experience in a manufacturingenvironment.
  • Experiencecontributing to manufacturing improvement projects, with demonstratedresults in throughput, productivity, labor efficiency, quality, oroperating costs.
  • Experienceconducting time studies, analyzing labor requirements and productioncapacity, and identifying process improvement opportunities.
  • Practicalexperience applying Lean manufacturing methods, such as Kaizen, valuestream mapping, standard work, and waste elimination.
  • Stronganalytical and problem-solving skills, with experience using manufacturingperformance data to develop recommendations and evaluate results.
  • Proficiencywith Microsoft Excel and data analysis tools.
  • Strongcommunication skills and demonstrated ability to collaborate withproduction employees and cross-functional teams.
  • Legalauthorization to work in the United States.
Preferred Qualifications:
  • Experiencein electrical products manufacturing or high-volume assembly operations.
  • Experiencesupporting Lean operating systems.
  • LeanSix Sigma Green Belt or equivalent continuous improvement certification.
  • Experiencesupporting FPY improvements through root cause analysis, error-proofing,or process standardization.
  • Experiencewith Microsoft Power BI, Minitab, or other manufacturing analytics tools.
  • Experiencedeveloping labor standards, balancing production lines, or maintainingcapacity models
  • Experienceimplementing ergonomic improvements and reducing safety risks inmanufacturing environments.

#LI-EP1

#LI-ONSITE

About Siemens:

We are a global technology company focused on industry,
infrastructure, transport, and healthcare. From more resource-efficient
factories, resilient supply chains, and smarter buildings and grids, to
sustainable transportation as well as advanced healthcare, we create technology
with purpose adding real value for customers. Learn more about Siemens here.

Our Commitment to Equity and Inclusion in our DiverseGlobal Workforce:

We value your unique identity and perspective. We are fully
committed to providing equitable opportunities and building a workplace that
reflects the diversity of society, while ensuring that we attract the best
talent based on qualifications, skills, and experiences. We welcome you to
bring your authentic self and transform the everyday with us.

63,393 108,674

Organization: Smart Infrastructure

Job Type: Full-time

Category: Manufacturing

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