Lead, Manufacturing Analytics

Lead, Manufacturing Performance Analytics

Entegris seeks a highly motivated Manufacturing Performance Analytics Lead to support our Advanced Purity Solutions division. The Lead is accountable for enabling data‑driven operational decision‑making by delivering standardized, scalable analytics that provide clear visibility of manufacturing performance across sites.

The Manufacturing Performance Analytics Lead is responsible for defining and owning core execution metrics, dashboards, and analytic views across capacity, throughput, WIP, cycle time, yield, and on‑time shipment. This includes ensuring alignment with standardized master data and execution processes.

• Develop strong technical knowledge of data architecture across business systems, especially ERP, SPC, LIMS, and cloud databases.
• Gain working knowledge of processes and operations across multiple sites and business units to contextualize data and deliver impactful visualizations to site operations teams.
• Partner closely with Operations, Engineering, Planning, and Digital teams to translate business questions into actionable analytics.
• Ensure consistent metric definitions and targets by functional area, and drive adoption of visual management tools to identify constraints, prioritize actions, and proactively manage performance at the shop floor, site, and network levels.
• Collaborate with local and global stakeholders to build out Daily Operations Cockpits – dashboards aligned to key functions within the operations organization.
• Identify opportunities to bring new data sets into the Google Cloud Platform data lake for use in the Operations Cockpits, process controls, and predictive analyses.
• Construct predictive analysis dashboards, pulling together and transforming data sets related to raw material, production process, and finished goods to solve technical problems and inform business decisions.
• Maintain global scalability of dashboards and data structures to enable translation to other sites and units.
• Build and maintain relationships across the global organization to enable effective leadership and collaboration with data visualization teams.
• Communicate effectively across the organization (BU, Operations, NPI, NPD, R&D, etc.) to drive results and contribute to the department’s direction with leadership.
• Wear PPE as necessary for work in a cleanroom and lift up to 50 lbs.

• Bachelor of Science in Engineering, Data Science, or similar.
• 10+ years of experience in operations/manufacturing data support roles.
• Data manipulation and visualization skills using Power BI, Tableau, or similar.
• Understanding of SPC and its application in manufacturing a plus.
• Desire to collaborate with varied cross‑functional stakeholders at all levels.
• Tenacity to drive projects to completion, translating broad requirements into specific functionality or visuals to meet business needs.
• Ability to maintain positive collaborative working relationships with cross‑functional stakeholders at all levels.
• Ability to present technical data to all levels of the organization.
• Ability to travel domestically and/or internationally in support of Global Process Engineering team charter (up to 20%).

• Standardized Manufacturing Performance Visibility.
• Clear definition, documentation, and consistent application of core execution metrics across supported sites.
• Dashboards that provide accurate, timely, and trusted visibility into manufacturing performance at shop floor, site, and network levels.
• Actionable analytics adoption by Operations, Engineering, Planning, and other stakeholders.
• Integration of Visual Management Tools, including Daily Operations Cockpits, into routine operational reviews to enable proactive performance management.
• Scalable and sustainable analytics solutions designed for global scalability.
• Integration of new and existing data sets into the Google Cloud Platform data lake to support analytics, process controls, and predictive analysis.
• Predictive analytics that inform business decisions and address technical challenges.
• Analytics outputs supporting problem identification, root cause analysis, and operational performance…