Manufacturing Data and Analytics Manager

Position Summary

The Manufacturing Data and Analytics Manager leads Daisy Brand's manufacturing data strategy across all facilities, driving the use of data, analytics, and Manufacturing Execution Systems (MES) to improve operational performance, visibility, and decision-making. This role is responsible for developing, implementing, and governing data systems and analytics capabilities that enhance efficiency, quality, and reliability in a food and beverage manufacturing environment.

The Manufacturing Data and Analytics Manager leads Daisy Brand's manufacturing data strategy across all facilities, driving the use of data, analytics, and Manufacturing Execution Systems (MES) to improve operational performance, visibility, and decision-making. This role is responsible for developing, implementing, and governing data systems and analytics capabilities that enhance efficiency, quality, and reliability in a food and beverage manufacturing environment.

This position directly leads the established MES team through the MES Team Leader and will build out a new Manufacturing Data Analyst team, providing both strategic direction and hands-on leadership to ensure the successful deployment and sustainment of digital manufacturing initiatives. This is a growing function at Daisy Brand, and this role will play a central part in shaping its structure, capabilities, and direction from the ground up.

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.

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).

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.

• 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.

• 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.

• 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.

• 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…