About the Company

Our client is the U.S. market leader in multiple food categories and has built an exceptional reputation for taking care of its employees. The company treats its people like gold, reflected in an average 14-year tenure among technical and engineering team members.

Employees receive 100% company-paid medical insurance and five weeks of vacation, along with the opportunity to work for a financially strong, growing manufacturing organization investing heavily in technology, automation, data, and its people.

This position can be based in Dallas, TX; Phoenix/, OH or IA. - It can be Hybrid for awhile until the person can move. 

Position Summary

The Manufacturing Data & Analytics Manager will lead the company's manufacturing data, analytics, and MES strategy across multiple manufacturing facilities.

This is both a strategic and hands-on leadership position. The manager will lead the existing MES team through an MES Team Leader and build a new Manufacturing Data Analyst team. The role will establish consistent manufacturing data standards, improve MES capabilities, develop analytics that directly improve plant performance, and connect shop-floor systems with enterprise data platforms.

The successful candidate must understand manufacturing operations and technology—not just data analytics. They must be able to work directly with plant operations, engineering, IT, automation, and data teams to turn manufacturing data into measurable improvements in production, quality, yield, downtime, and overall equipment effectiveness.

US CITZENSHIP REQUIRED 

Core & Key Responsibilities

Manufacturing Data & Analytics

• Develop and implement the company's manufacturing data strategy across all plants.
• Establish standardized manufacturing KPIs, data models, reporting, and measurement methods across facilities.
• Develop dashboards and analytics for OEE, throughput, yield, downtime, quality, production performance, and other plant KPIs.
• Analyze manufacturing data to identify performance problems, trends, root causes, and opportunities for improvement.
• Provide plant leadership with actionable information—not simply reports or raw data.
• Develop capabilities for predictive analytics, including predictive maintenance and statistical analysis.

MES Leadership & Ownership

• Own the MES roadmap, implementation, configuration, governance, and continuous improvement across the manufacturing network.
• Ensure MES supports production reporting, quality, traceability, downtime tracking, performance management, and other manufacturing requirements.
• Lead integration between MES and ERP, PLC/SCADA, historians, automation systems, and enterprise data platforms.
• Establish standards for MES data accuracy, integrity, utilization, and system changes.
• Ensure MES requirements are incorporated into new equipment, automation, and capital projects.

Data Architecture & Integration

• Define how manufacturing data is collected, structured, stored, integrated, and made available for analysis.
• Work with IT and Enterprise Data teams to build reliable and scalable manufacturing data infrastructure.
• Ensure effective data flow from shop-floor automation and control systems through MES and into enterprise analytics platforms.
• Address data security, reliability, governance, and cybersecurity requirements associated with manufacturing systems.

Team Leadership

• Lead and develop the existing MES organization through the MES Team Leader.
• Build and manage a new team of Manufacturing Data Analysts.
• Define team structure, responsibilities, priorities, performance expectations, and technical capabilities.
• Recruit, develop, and retain technical personnel capable of supporting manufacturing analytics and digital manufacturing initiatives.

Plant & Cross-Functional Leadership

• Work directly with Operations, Engineering, Quality, Supply Chain, IT, and plant leadership to identify and prioritize manufacturing data opportunities.
• Participate in plant performance reviews and continuous improvement initiatives.
• Ensure technology and data initiatives produce measurable operational and financial results.
• Evaluate the business case and ROI for manufacturing analytics, MES, and digital technology investments.

Qualifications — Required for the Job

• Bachelor's degree in Engineering, Computer Science, Data Analytics, Information Technology, or a closely related technical field.
• 8–12+ years of experience working with manufacturing data, analytics, MES, digital manufacturing, manufacturing systems, or a closely related discipline.
• Demonstrated experience leading manufacturing technology or data initiatives across multiple manufacturing facilities.
• Strong hands-on experience with MES platforms, such as AVEVA/Wonderware, Rockwell, Siemens, or comparable systems.
• Working knowledge of manufacturing operations, OEE, throughput, yield, downtime, quality, production reporting, and continuous improvement.
• Experience integrating manufacturing systems, including MES, ERP, PLC/SCADA, historians, automation systems, and enterprise data platforms.
• Experience developing or overseeing manufacturing dashboards, reporting, data models, and analytics.
• Previous experience leading technical teams, including hiring, developing, prioritizing, and managing technical personnel.
• Ability to work directly with plant managers, engineering leaders, IT, automation personnel, and data/analytics professionals.
• Ability to take complex manufacturing data and translate it into specific operational actions and measurable business results.
• Strong understanding of data governance, data integrity, system security, and change management within a manufacturing environment.
• Experience evaluating the financial return and business value of technology and digital manufacturing investments.

Preferred Background

Preference will be given to candidates with experience in food & beverage, consumer packaged goods (CPG), pharmaceutical, or other highly automated process manufacturing environments, particularly those who have managed manufacturing data and MES systems across multiple plants.