Manufacturing Data and Analytics Manager

Position Summary

Location and Travel Requirements

• Travel Requirements: Approximately 25 to 40 percent to manufacturing facilities and vendor sites.
• Daisy Brand is hiring for one Manufacturing Data and Analytics Manager. This role can be located at any of our manufacturing locations in Dallas/Garland, TX; Boone, IA, Wooster, OH; or Casa Grande, AZ.

For candidates interested in our Dallas, TX location

• Currently, the Daisy Brand corporate office is located in Dallas, TX at 635 and 75. Anticipated September 2027, we will be moving to the Granite Park business complex in North Plano (intersection of Dallas North Tollway and Sam Rayburn Tollway).

For candidates interested in our Boone, IA location

• The position is currently located at a temporary office in Ames, IA. Expected in 2028, upon completion of construction, the position will be moving to be onsite at our new manufacturing plant in Boone, IA.
• This position operates under a hybrid work model, requiring onsite presence Monday, Tuesday, and Thursday, with Wednesday and Friday designated as remote workdays. While this schedule is typical, team or business needs may require additional onsite days.
• Key Responsibilities
• Manufacturing Data and Analytics Leadership
• Develop and execute a corporate manufacturing data strategy aligned with business and operational goals.
• Lead the design and deployment of analytics solutions that improve key performance indicators such as OEE, throughput, yield, downtime, and quality.
• Establish standardized data models, KPIs, and reporting frameworks across all manufacturing facilities.
• Promote a data-driven culture through training, tools, and strong cross-functional engagement.
• MES System Ownership and Governance
• Own the roadmap, implementation, and continuous improvement of MES platforms across the enterprise.
• Ensure MES systems are configured to support production, quality, traceability, and performance management requirements.
• Partner with IT, Engineering, Operations, and the Enterprise Data and Analytics Team to align MES architecture and integrate MES with ERP, automation systems, historians, and other digital platforms.
• Establish governance standards for MES data integrity, accuracy/reasonableness, system utilization, and change management.
• Analytics and Performance Optimization
• Lead development of dashboards, reports, and advanced analytics solutions that enable real-time and predictive insights.
• Analyze manufacturing data to identify trends, root causes, and opportunities for continuous improvement.
• Support plant teams with actionable insights to reduce downtime, improve yield, and optimize processes.
• Drive adoption of advanced analytics techniques, including predictive maintenance and statistical modeling.
• Collaborate with the Enterprise Data and Analytics Team to ensure alignment on tools, data pipelines, and enterprise reporting strategies.
• Data Architecture and Integration
• Define and maintain the manufacturing data architecture, including data collection, storage, and accessibility standards.
• Ensure integration of shop floor systems (PLC/SCADA), MES, and enterprise systems for seamless data flow.
• Collaborate with IT and Enterprise Data teams to ensure a secure, scalable, reliable, and well-governed data infrastructure, including cybersecurity considerations.
• Team Leadership and Development
• Lead, mentor, and develop the MES Team Leader and the existing MES team.
• Hire, onboard, and develop the new Manufacturing Data Analyst team, defining the roles and structure needed to support the data strategy.
• Build team capabilities in analytics, data engineering, and manufacturing systems.
• Establish clear roles, priorities, and performance expectations aligned with business needs.
• Cross-Functional Collaboration
• Partner with Engineering, Operations, Quality, Supply Chain, and IT to align data initiatives with operational and enterprise priorities.
• Support capital projects by ensuring data and MES requirements are included in equipment and system design.
• Participate in plant reviews, performance meetings, and continuous improvement initiatives.

Qualifications and Requirements

• Education and Experience
• Bachelor's degree in Engineering, Data Analytics, Computer Science, or a related field; advanced degree preferred.
• 8 to 12 or more years of experience in manufacturing data, analytics, or digital manufacturing roles, with preference given to food and beverage, CPG, and pharmaceutical manufacturing environments.
• Strong experience with MES platforms (for example, AVEVA/Wonderware, Rockwell, Siemens) and manufacturing data systems.
• Experience managing teams and delivering multi-site digital manufacturing initiatives.
• Skills and Competencies
• Strong understanding of manufacturing operations, KPIs (OEE, downtime, yield), and continuous improvement principles.
• Proven ability to translate complex data into actionable insights for operations teams.
• Strong leadership and communication skills, with the ability to influence and collaborate across Engineering, IT, and Enterprise Data organizations.
• Experience with data visualization tools, databases, and analytics tools.
• Knowledge of system integration, industrial automation, and data governance best practices.
• Financial acumen with the ability to evaluate the return on investment of digital and analytics investments.