Sr Manager Data Analytics Logistics & Procurement at Tyson Foods in Corporate 412 West - Springdale, Arkansas

Job description

• * This position will sit 100% onsite at out Corporate 412 West location. *
• ** Priority consideration will be given to those who currently reside within a 50-mile radius of Springdale, AR. **
• The Sr Manager Data Analytics Logistics & Procurement leads the design and delivery of high-value, complex analytics, artificial intelligence, automation, and data engineering solutions across Logistics and Procurement. This role combines deep technical expertise with business acumen to translate operational challenges into scalable data products, intelligent applications, and automated solutions that deliver measurable business value.
• The Sr Manager provides hands-on technical leadership across advanced analytics and data engineering — including solution architecture, data pipelines and modeling, AI-enabled applications, system integrations, and workflow automation. The role owns initiatives end to end, from problem identification and technical design through development, production implementation, adoption, and value realization.
• The Sr Manager works closely with Logistics and Procurement leaders, senior leadership, and data and analytics teams across Tyson to identify and implement the tools, platforms, and practices needed to deliver continued value to stakeholders. This includes partnering with IT and enterprise technical teams to ensure the security, reliability, and scalability of Tyson data.

Responsibilities

• Strategy and Business Partnership
• Business Partnership. Partner directly with Logistics and Procurement leaders and operational teams to understand business processes, identify opportunities, and translate operational challenges into technical requirements and solutions.
• Strategy and Roadmap. Collaborate with senior leadership to define strategy and roadmaps that align analytics, AI, and automation initiatives with broader business priorities, and evaluate emerging technologies to determine where new capabilities can practically create value.
• Business Case Development. Develop business cases, quantify opportunities, establish expected ROI and success measures, and communicate recommendations and value to business and senior leadership.
• Solution Delivery and Technical Leadership
• Initiative Leadership. Lead complex, high-value analytics, AI, automation, and data engineering initiatives from opportunity identification and requirements development through technical design, implementation, adoption, and value realization.
• Solution Architecture and Standards. Design and guide scalable solutions — data pipelines and models, integrations, analytics applications, automated workflows, and AI-enabled capabilities — and establish the reusable technical patterns and development practices that allow the team to efficiently build, deploy, monitor, and scale them.
• AI and Advanced Analytics. Develop and operationalize AI and advanced analytics solutions that improve decision-making, automate processes, identify exceptions, and surface actionable insights.
• Hands-On Delivery. Contribute directly through solution development, prototyping, architecture and code reviews, and troubleshooting, applying agile practices to deliver on time and to quality standards.
• Team Leadership and Development
• Lead and Develop the Team. This position is considered an individual contributor and does not have direct reports. However, it will be required to partner with organizational leaders to support their teams in development of analytics, data engineering, and technical talent by providing coaching, expertise, and developmental opportunities that enhance skills, broaden cross-functional exposure, and foster career growth within a collaborative and innovative culture.
• Technical Mentorship. Mentor analysts, data engineers, and team leads on advanced technical techniques, solution reviews, and problem-solving, and share knowledge broadly to expand team capability.
• Operational Excellence and Governance
• Enterprise Collaboration. Collaborate with IT and enterprise technical teams on architecture, infrastructure, security, integration, governance, and production deployment, driving solutions forward from the Logistics and Procurement business perspective.
• Operational Performance and Risk. Drive operational improvements across the team and oversee risk management processes that proactively address issues and implement mitigation strategies.
• Stakeholder and Vendor Management. Maintain frequent, effective communication with cross-functional teams and stakeholders, and evaluate and manage relationships with vendors and service providers to ensure successful partnerships.
• Value Realization. Measure solution adoption, operational impact, financial value, and reliability following implementation.
• This role will also perform other job-related duties as assigned that align with the organization’s vision, mission, and values and fall within the scope of the role.

Requirements

• Education
• Bachelor’s degree in Computer Science, Data Science, Engineering, Analytics, Information Systems, Supply Chain Management, Business, or a related field is preferred. Master’s degree is strongly preferred. Seven years of relevant experience will also be considered in place of a degree.
• Relevant certifications in data engineering, cloud technologies, AI, machine learning, automation, analytics, or related disciplines are preferred but not required.
• Experience
• Seven years+ of relevant, practical experience in data engineering, analytics engineering, artificial intelligence, automation, software development, advanced analytics, analytics management, or a related technical field, with a proven ability to lead and motivate teams.
• Demonstrated experience designing and delivering complex, production-ready data or technology solutions is strongly preferred. Experience applying technology within logistics, procurement, supply chain, warehousing, manufacturing, or another operationally intensive environment is preferred.
• Special Skills
• Technical Depth. Strong knowledge of modern data engineering and architecture — data pipelines, modeling, orchestration, integrations, cloud data environments, and scalable solution design — along with proficiency in scripting or software development and familiarity with APIs, version control, testing, monitoring, and security.
• AI and Automation Fluency. Strong understanding of modern AI, machine learning, and intelligent automation, and of the data and application patterns required to turn these capabilities into practical business solutions.
• Problem-Solving and Decision-Making. Ability to independently structure ambiguous problems, investigate technical and data challenges, evaluate alternatives, and make sound decisions under pressure.
• Business and Technical Translation. Ability to understand operational processes and translate between business requirements, data needs, technical architecture, and measurable business outcomes.
• Leadership and Delivery Management. Strong leadership and proficiency in project management methodologies and tools, and the ability to set technical direction and gain alignment across business stakeholders, engineers, IT teams, and senior leadership.
• Communication and Interpersonal Skills. Ability to clearly explain complex technical concepts, recommendations, opportunities, and risks to both technical and non-technical audiences, ensuring alignment and understanding at all levels.

Skills

Required

• Leadership
• Communication and interpersonal skills
• Problem-solving and decision-making
• Business and technical translation
• Team leadership and development
• Mentorship
• Data engineering
• Analytics engineering
• Artificial intelligence
• Machine learning
• Automation
• Software development

Benefits

• We provide our team members and their families with paid time off; 401(k) plans; affordable health, life, dental, vision and prescription drug benefits; and more.