Senior Manager Data Analytics Logistics & Procurement

Job Details:

* RESUME REQUIRED TO BE CONSIDERED FOR THIS ROLE *

The Senior Manager Data Analytics Logistics & Procurement develops standards, tools, and governance for capturing, modeling, storing, and delivering data for Logistics, including:

• Identifying AI and data-related business requirements and service standards (e.g., transaction processing speed, data mining and reporting capabilities, data security, scalability, etc.).
• Developing high-level enterprise data models and conceptual views of related data sub-architectures (e.g., database, data integration, data warehouse/business intelligence, reporting, metadata, and content management architectures).
• Optimizing overall data/information flow by reducing redundancy and enabling accessibility within security boundaries.
• Implement and deliver AI strategy, solutions, and literacy across the Logistics organization.

Senior Manager Data Analytics Logistics & Procurement oversees one or more Data Engineering Disciplines. This is an individual contributor role.

Essential Duties and Responsibilities

Technical Standards and Governance:
• Establishing and maintaining enterprise-wide technical standards, guidelines, and best practices for software development, quality, and infrastructure.
• Ensuring compliance with these standards across all programs and projects.
• Perform other assigned job-related duties that align with our organization's vision, mission, and values and fall within your scope of practice.

Architecture Design and Review:
• Designing scalable, reliable, and secure architecture solutions that align with business goals and technical requirements.
• Conducting architecture reviews and providing guidance to ensure alignment with enterprise standards with regards to the citizen development framework.

Cross-Disciplinary Expertise:
• Leveraging expertise in software development, quality engineering, and infrastructure engineering to provide holistic architectural solutions.
• Ensuring seamless integration of development, quality, and infrastructure components.

Technology Evaluation and Selection:
• Evaluating and selecting appropriate technologies, AI models, tools, and platforms aligned with enterprise standards and business needs.
• Conducting proof-of-concept (PoC) projects to validate technology choices.

Collaboration and Communication:
• Collaborating with development, quality, and infrastructure teams to ensure alignment with enterprise architecture standards.
• Facilitating communication and knowledge sharing across teams and departments

Continuous Improvement:
• Promoting a culture of continuous improvement by identifying opportunities to enhance technical standards and practices.
• Staying up to date with industry trends and emerging technologies to ensure the enterprise remains competitive.

Performance and Scalability:
• Designing solutions that ensure high performance, scalability, and reliability.
• Conducting performance assessments and optimizations to meet enterprise requirements.

Disaster Recovery and Business Continuity:
• Ensuring that all architectural solutions include robust backup and recovery mechanisms.

Quality Assurance and Testing:
• Ensuring that automated testing, continuous integration, and continuous deployment (CI/CD) practices are implemented and consistently applied.

Documentation and Knowledge Management:
• Creating and maintaining comprehensive architectural documentation, including diagrams, standards, and guidelines.
• Ensuring that documentation is accessible and up to date for all stakeholders.

Vendor and Tool Management:
• Manage relationships with technology vendors and ensure that tools and services meet enterprise and Logistics standards.
• Evaluating and integrating third-party solutions as needed.

Incident Management and Troubleshooting:
• Providing high-level support for incident management and troubleshooting complex technical issues.
• Conducting root cause analysis and implementing preventive measures.

Capacity Planning and Resource Management:
• Conducting capacity planning ensures enterprise architecture can handle current and future workloads.
• Managing resources effectively to support enterprise-wide and Logistic initiatives.

Training and Mentorship:
• Providing training and mentorship to technical and non-technical teams to ensure adherence to enterprise standards.
• Supporting professional development and knowledge sharing within the organization.

Qualifications:

Education: Bachelor's Degree or relevant experience. Computer Science, Computer Engineering, Information Systems, Quantitative or Engineering Field preferred.

Experience: 7+ years of relevant and practical experience.

Special Skills Required:
• Deep technical expertise in one or more areas of focus, e.g., Data Engineering, Data Modeling, Data Platforms, Data Visualization, Automation, AI
• The ability to explain highly technical concepts to non-technical team members and leaders.
• Self-driven ability to vet new technical patterns, influence decision-makers, and establish those patterns as new technical standards.

Relocation Assistance Eligible:

No

Work Shift:

1ST SHIFT (United States of America)

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Hourly Applicants ONLY -You must complete the task after submitting your application to provide additional information to be considered for employment.

The successful candidate(s) must be willing and able to perform the physical requirements of the job with or without a reasonable accommodation.

Tyson is an Equal Opportunity Employer. All qualified applicants will be considered without regard to race, national origin, color, religion, age, genetics, sex, sexual orientation, gender identity, disability or veteran status.

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.

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