oracle
Industrial Engineer - Senior
Cummins Inc.
Pune, IND
Full-time
Senior
Discovered 3 weeks ago
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Key Skills for This Role
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Qualifications
- Job Description: Industrial Engineer Senior
- Role Summary: We are seeking an Industrial Engineering professional with strong expertise in discrete manufacturing, industrial engineering, and data analytics. This role will transform manufacturing data into actionable insights, drive continuous improvement, and support the deployment of AI and analytics solutions across plant operations.
- Analyze data from digital manufacturing systems such as CMES, Connected Factory, Maximo, Q-DAS, OEE platforms, and other plant applications to identify improvement opportunities.
- Partner with Operations, Manufacturing Engineering, Maintenance, Quality, and Supply Chain teams to understand process challenges and convert them into data-driven improvement projects.
- Develop dashboards, analytics models, and performance insights to improve productivity, equipment utilization, quality, cost, and operational efficiency.
- Support AI and machine learning use cases by providing manufacturing domain expertise, validating data logic, and helping enterprise AI teams translate plant requirements into practical solutions.
- Perform data validation, root-cause analysis, and performance investigations using SQL, Python, Power BI, and other analytics tools.
- Identify bottlenecks, waste, process variation, and reliability issues, then recommend practical actions to drive measurable business improvements.
- Facilitate Industry 4.0 analytics workshops, train plant teams on analytics tools, and build capability for data-driven decision making.
- Design and support Operations Control Tower concepts by integrating data from manufacturing, maintenance, quality, and ERP systems to provide a consolidated view of operations.
- Bachelor’s degree in industrial engineering, Manufacturing Engineering, Mechanical Engineering, Production Engineering, or a related field.
- Strong understanding of discrete manufacturing processes, plant operations, lean manufacturing, industrial engineering methods, and continuous improvement practices.
- Hands-on experience with manufacturing performance metrics such as OEE, throughput, downtime, cycle time, productivity, quality losses, and cost improvement.
- Proficiency in data analytics tools and methods, including SQL, Python, Power BI, statistical analysis, and data visualization.
- Ability to work with large operational data sets, validate data quality, identify trends, and convert analysis into business actions.
- Experience collaborating with cross-functional plant teams and translating shop-floor challenges into analytics or AI use cases.
- Strong communication, stakeholder management, problem-solving, and project execution skills.
- Experience in Industry 4.0, smart manufacturing, connected factory, MES, ERP, or digital manufacturing platforms.
- Exposure to AI, machine learning, predictive analytics, or advanced operations analytics in a manufacturing environment.
- Experience leading value stream improvement, or data-driven productivity projects.
- Ability to influence plant stakeholders and drive adoption of analytics-based improvement actions.
Key Responsibilities
- Analyze data from digital manufacturing systems such as CMES, Connected Factory, Maximo, Q-DAS, OEE platforms, and other plant applications to identify improvement opportunities.
- Partner with Operations, Manufacturing Engineering, Maintenance, Quality, and Supply Chain teams to understand process challenges and convert them into data-driven improvement projects.
- Develop dashboards, analytics models, and performance insights to improve productivity, equipment utilization, quality, cost, and operational efficiency.
- Support AI and machine learning use cases by providing manufacturing domain expertise, validating data logic, and helping enterprise AI teams translate plant requirements into practical solutions.
- Perform data validation, root-cause analysis, and performance investigations using SQL, Python, Power BI, and other analytics tools.
- Identify bottlenecks, waste, process variation, and reliability issues, then recommend practical actions to drive measurable business improvements.
- Facilitate Industry 4.0 analytics workshops, train plant teams on analytics tools, and build capability for data-driven decision making.
- Design and support Operations Control Tower concepts by integrating data from manufacturing, maintenance, quality, and ERP systems to provide a consolidated view of operations.
- Required Skills & Qualifications
- Bachelor’s degree in industrial engineering, Manufacturing Engineering, Mechanical Engineering, Production Engineering, or a related field.
- Strong understanding of discrete manufacturing processes, plant operations, lean manufacturing, industrial engineering methods, and continuous improvement practices.
- Hands-on experience with manufacturing performance metrics such as OEE, throughput, downtime, cycle time, productivity, quality losses, and cost improvement.
- Proficiency in data analytics tools and methods, including SQL, Python, Power BI, statistical analysis, and data visualization.
- Ability to work with large operational data sets, validate data quality, identify trends, and convert analysis into business actions.
- Experience collaborating with cross-functional plant teams and translating shop-floor challenges into analytics or AI use cases.
- Strong communication, stakeholder management, problem-solving, and project execution skills.
- Preferred Experience
- Experience in Industry 4.0, smart manufacturing, connected factory, MES, ERP, or digital manufacturing platforms.
- Exposure to AI, machine learning, predictive analytics, or advanced operations analytics in a manufacturing environment.
- Experience leading value stream improvement, or data-driven productivity projects.
- Ability to influence plant stakeholders and drive adoption of analytics-based improvement actions.
- Looking at the data we gather from multiple systems, this position will add value in bringing meaningful insights for effective operations.
- Competencies: Communicates effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences. Ergonomic Fundamentals - Understands ergonomic concepts by applying Cummins ergonomic standards, guidelines, controls and tools to reduce ergonomic risk to employees while at work. Health and Safety Fundamentals - Champions and models proactive health and safety behaviors by identifying, reporting and participating in actions t
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