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Land O'Lakes Inc
Product Owner, Enterprise Manufacturing Systems
Career Insights for Chief Digital Transformation Officer
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Based on Minnesota data
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What they do
A Chief Digital Transformation Officer is the company executive responsible for leading it through a process of rapid technology change, often updating out-of-date business processes or business models.
$162,350 / year median in Minnesota
+8% projected growth
Job Description
Product Owner, Enterprise Manufacturing Systems We are seeking a Product Owner, Enterprise Manufacturing Systems to lead the enterprise strategy and delivery of manufacturing systems that enable connected, data-driven operations across our manufacturing network. This Senior Manager serves as the enterprise owner and integration leader for manufacturing systems that connect physical manufacturing operations to business processes, analytics, and digital transformation outcomes. This role translates plant needs and Digital Manufacturing strategy into practical capabilities that improve execution, visibility, traceability, yield, downtime management, quality, throughput, and data-driven performance management. This role will lead and develop a high-performing team of technology professionals by fostering a culture of collaboration, innovation, and continuous improvement. The ideal candidate brings strong manufacturing systems expertise, operational credibility, cross-functional leadership, and the ability to partner across controls engineering, operations, IT, cybersecurity, and analytics to execute the Digital Manufacturing strategy. Key Responsibilities in this role will include: 1. Enterprise Manufacturing Systems Strategy and Roadmap
- Own and maintain the enterprise roadmap for ERP manufacturing capabilities, plant-floor data collection, historians, integration platforms, and related digital manufacturing solutions.
- Translate Digital Manufacturing strategy into scalable system capabilities, deployment plans, standards, and governance practices.
- Define where capabilities should reside across ERP, MES, SCADA, historian, edge, integration, enterprise data platform, and analytics layers.
- Rationalize legacy or redundant manufacturing applications and drive standardization across sites where appropriate.
- Prioritize investments based on business value, risk reduction, operational readiness, technical feasibility, and scalability. 2. ERP Manufacturing Process Integration
- Represent manufacturing needs in ERP process design, including process orders, bills of material, recipes, routings, confirmations, goods issue, goods receipt, inventory movements, batch management, and traceability.
- Partner with Operations and SC Engineering teams to define how ERP manufacturing functionality should interact with MES, SCADA, historians, warehouse systems, quality systems, and data platforms.
- Improve manufacturing master data quality and governance required for digital execution and analytics.
- Support ERP transformation programs by ensuring plant-level execution needs are understood and incorporated into end-to-end designs. 3. Plant-Floor Data Collection and OT/IT Integration
- Define strategy and standards for collecting data from PLCs, SCADA, historians, sensors, equipment systems, operator inputs, lab systems, and other manufacturing sources.
- Ensure plant-floor data is contextualized with production orders, materials, assets, lines, shifts, batches, downtime events, quality results, and operational states.
- Partner closely with Controls Engineering to align on tag standards, asset hierarchy, historian strategy, connectivity patterns, data ownership, and operational reliability.
- Partner with Technology teams to establish secure, scalable OT/IT integration patterns using appropriate mechanisms such as historians, OPC, MQTT, APIs, edge platforms, or middleware.
- Partner with Manufacturing Analytics to ensure systems produce accurate, contextualized, analytics-ready data for reporting, data engineering, data science, and visualization. 4. Program Delivery, Governance, and Adoption
- Lead cross-site implementation programs including requirements, solution design, testing, deployment planning, training, change management, hypercare, and support transition.
- Establish governance forums, intake processes, prioritization methods, decision rights, and system lifecycle management practices.
- Build strong partnerships with plant leadership, operators, supervisors, quality, maintenance, engineering, supply chain, IT, and external vendors.
- Ensure systems comply with cybersecurity, access control, business continuity, data governance, and enterprise architecture requirements.
- Build and lead a capable team of software engineers, business analysts, implementation resources, and platform support partners.
Required Qualifications:
- Bachelor degree in Engineering, Computer Science, Information Systems, Operations Management, or a related field, or equivalent practical experience.
- 8 or more years of experience in digital manufacturing, manufacturing execution systems, supply chain technology, or related manufacturing roles.
- Experience leading cross-functional supply chain technology programs across multiple sites or business units.
- Strong understanding of manufacturing operations, production execution, material flow, quality processes, traceability, yield, downtime, and operational performance metrics.
- Experience partnering with controls engineering, plant operations, IT, cybersecurity, enterprise architecture, analytics, and external vendors.
- Demonstrated ability to translate business requirements into scalable technology capabilities and practical implementation plans.
- Experience serving as a product or capability owner for digital systems, including roadmap ownership, backlog prioritization, stakeholder alignment, value realization, and governance of manufacturing technology products.
- Proven people leadership, stakeholder management, vendor management, and program delivery capability.
- Ability to travel up to 25% of the time.
Preferred Qualifications:
- Experience enabling manufacturing data into Snowflake or other enterprise data platforms.
- Familiarity with data engineering concepts, manufacturing analytics, Power BI or Tableau, and common manufacturing data models.
- Understanding of OT cybersecurity, network segmentation, access control, disaster recovery, and support models for manufacturing environments.
- Experience building governance, capability models, templates, standards, and deployment playbooks across a manufacturing network.