Sr Manager Data Analytics Logistics & Procurement

Tyson Foods•Springdale, AR

12d•Onsite

About The Position

The Sr Manager Data Analytics Logistics & Procurement leads the design and delivery of complex analytics, artificial intelligence, automation, and data engineering solutions for Logistics and Procurement. The role combines technical expertise and business acumen to turn operational challenges into scalable data products, intelligent applications, and automated solutions that deliver measurable business value. It provides hands-on technical leadership in solution architecture, data pipelines and modeling, AI-enabled applications, system integrations, and workflow automation. The position owns initiatives from problem identification and design through development, production implementation, adoption, and value realization. The Sr Manager partners with Logistics and Procurement leaders, senior leadership, and Tyson data and analytics teams to identify and implement tools, platforms, and practices that deliver value to stakeholders. The role also collaborates with IT and enterprise technical teams on the security, reliability, and scalability of Tyson data. This is an individual contributor position with no direct reports, though it provides technical mentorship and supports talent development across teams. The position is 100% onsite at the Corporate 412 West location, with priority consideration for candidates residing within 50 miles of Springdale, Arkansas. Travel is 1–3 trips per year, and the role is on first shift.

Requirements

Seven or more years of relevant practical experience in data engineering, analytics engineering, artificial intelligence, automation, software development, advanced analytics, analytics management, or a related technical field.
Proven ability to lead and motivate teams; this position has no direct reports.
Strong knowledge of modern data engineering and architecture, including data pipelines, modeling, orchestration, integrations, cloud data environments, and scalable solution design.
Proficiency in scripting or software development and familiarity with APIs, version control, testing, monitoring, and security.
Strong understanding of modern AI, machine learning, and intelligent automation, including the data and application patterns needed to turn these capabilities into practical business solutions.
Ability to structure ambiguous problems independently, investigate technical and data challenges, evaluate alternatives, and make sound decisions under pressure.
Ability to understand operational processes and translate between business requirements, data needs, technical architecture, and measurable business outcomes.
Strong leadership and proficiency in project management methodologies and tools; ability to set technical direction and gain alignment across stakeholders, engineers, IT teams, and senior leadership.
Ability to explain complex technical concepts, recommendations, opportunities, and risks to technical and non-technical audiences.
Willingness and ability to perform the physical requirements of the job, with or without reasonable accommodation.
A resume is required to be considered for the role.

Nice To Haves

Bachelor’s degree in Computer Science, Data Science, Engineering, Analytics, Information Systems, Supply Chain Management, Business, or a related field; seven years of relevant experience may be considered in place of a degree.
Master’s degree is strongly preferred.
Relevant certifications in data engineering, cloud technologies, AI, machine learning, automation, analytics, or related disciplines are preferred but not required.
Demonstrated experience designing and delivering complex, production-ready data or technology solutions.
Experience applying technology within logistics, procurement, supply chain, warehousing, manufacturing, or another operationally intensive environment.
Residence within a 50-mile radius of Springdale, Arkansas receives priority consideration.

Responsibilities

Partner with Logistics and Procurement leaders and operational teams to understand business processes, identify opportunities, and translate operational challenges into technical requirements and solutions.
Collaborate with senior leadership to define strategies and roadmaps aligned with business priorities, and evaluate emerging technologies for practical business value.
Develop business cases, quantify opportunities, establish expected ROI and success measures, and communicate recommendations and value to business and senior leadership.
Lead complex analytics, AI, automation, and data engineering initiatives from opportunity identification and requirements development through design, implementation, adoption, and value realization.
Design and guide scalable data pipelines, data models, integrations, analytics applications, automated workflows, and AI-enabled capabilities.
Establish reusable technical patterns and development practices for building, deploying, monitoring, and scaling solutions.
Develop and operationalize AI and advanced analytics solutions to improve decision-making, automate processes, identify exceptions, and surface actionable insights.
Contribute directly through solution development, prototyping, architecture and code reviews, and troubleshooting; apply agile practices to deliver on time and to quality standards.
Partner with organizational leaders to support development of analytics, data engineering, and technical talent through coaching, expertise, and developmental opportunities.
Mentor analysts, data engineers, and team leads on advanced technical techniques, solution reviews, and problem-solving; share knowledge to expand team capability.
Collaborate with IT and enterprise technical teams on architecture, infrastructure, security, integration, governance, and production deployment, advancing solutions from the Logistics and Procurement business perspective.
Drive operational improvements and oversee risk management processes to address issues and implement mitigation strategies.
Communicate with cross-functional teams and stakeholders, and evaluate and manage vendor and service-provider relationships.
Measure solution adoption, operational impact, financial value, and reliability after implementation.
Perform other job-related duties as assigned within the scope of the role.
Demonstrate responsible use of approved AI tools, safeguard sensitive information, follow company policies, validate AI-generated outputs, critically evaluate results, and apply professional judgment when using AI.