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Key skills for this role
To strengthen the Industrial Engineering function by leveraging data analytics, Power BI reporting, and standardized IE practices to enhance productivity, efficiency, and decision ‑ making across manufacturing.
The role will focus on developing data-driven insights to reduce throughput time, improve labour and machine utilization, and support continuous improvement initiatives.
This includes building and maintaining automated dashboards, establishing clear IE standards, and identifying improvement opportunities through advanced data modeling, statistical analysis, and visual reporting.
The position ensures that production processes consistently move toward world ‑ class performance through accurate, reliable, and actionable analytical outputs.
To strengthen the Industrial Engineering function by leveraging data analytics, Power BI reporting, and standardized IE practices to enhance productivity, efficiency, and decision ‑ making across manufacturing.
The role will focus on developing data-driven insights to reduce throughput time, improve labour and machine utilization, and support continuous improvement initiatives. This includes building and maintaining automated dashboards, establishing clear IE standards, and identifying improvement opportunities through advanced data modeling, statistical analysis, and visual reporting. The position ensures that production processes consistently move toward world ‑ class performance through accurate, reliable, and actionable analytical outputs.
Develop automated KPI dashboards (OEE, Efficiency, Waste %, Energy, Labour Utilization, Output per Shift) in Power BI, ensuring real-time insights and accurate reporting.
Identify continuous improvement opportunities using trend analytics, performance patterns, and statistical models.
Support cross-functional teams in implementing digital procedures.
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Design internal training material on Industrial Engineering basics, Lean Six Sigma, 5S, and proper working methods using data-driven insights.
Improve working practices to reduce material losses, non‑conformities, and process waste through targeted analytics.
Deploy Lean IE and Best Practice frameworks across all sites using a structured analytics‑assisted approach.
Ensure cross-department communication for implementing optimized manning models and change management initiatives.
Ensure efficient machine layout, ergonomics, and operator allocation using simulations, layout studies, and data-driven analysis.
Maintain clear, updated SOPs for standard setting, measurement methods, and Power BI reporting workflows.
Use S&OP data to project machine requirement (based on OEE), headcount requirement, and OHK forecasts; present insights during OCM meetings through interactive dashboards.
Support Quick Hits, Kaizens, and Lean Six Sigma projects with year‑on‑year improvement targets supported by data visualization and root cause analytics.
Register all CI projects in Power Steering; maintain project dashboards and ensure regular updates for monthly group reporting.
Ensure data integrity for all incentive schemes, productivity calculations, and plant-wide KPIs through robust data governance practices.
Use statistical tools, Power BI, and process analytics to highlight improvement opportunities proactively.
Experience working with MES / digital production monitoring systems.
Exposure to Digital Twin concepts, sustainability reporting (Higg FEM, ZDHC, etc.), or modern textile industry digital tools.
Ability to interpret machine-level data beyond manual entries and integrate them into Power BI dashboards.
Knowledge of structured data frameworks (JSON, APIs, automated data flows).
At Coats Group, we are committed to innovation, excellence, and fostering a diverse and collaborative environment where every team member can thrive. If you are passionate about making an impact in the textile industry and eager to join a global leader with a rich heritage and a forward-thinking approach, we invite you to take the next step in your career with us.
Verified company details for this employer are not available yet.
Full-time
Mid · 3+ years experience
Onsite
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