Data Engineer II

Tyson Foods•Springdale, AR

1d•Onsite

About The Position

Tyson Foods is seeking a Data Engineer II for its Inventory & Property Optimization (IPO) organization. The role spans data engineering, SAP systems, finance, inventory and asset management, and data governance, with a focus on accurate, reliable inventory and asset data aligned with enterprise standards. The Data Engineer II independently manages assignments of medium scope and complexity, provides day-to-day business and system support, and partners with teams across finance, operations, engineering, maintenance, supply chain, and technology. The position supports inventory accounting, valuation, cycle counts, physical inventory adjustments, construction-in-progress controls, capitalization metrics, maintenance and repair analytics, and reconciliation activities. It designs, configures, enhances, and supports SAP processes and data pipelines, and provides support for SaaS solutions used in inventory, maintenance, and asset lifecycle management. The role also supports master data standards, data governance, data quality reporting, documentation, user guides, and training materials, while translating technical findings into actionable recommendations. This is an on-site role; it is not remote. The position is based in the Springdale area, with priority consideration for qualified candidates living within 50 miles. Travel is approximately 25%–40%, depending on assignment. The position does not offer sponsorship or relocation benefits. The work shift is first shift.

Requirements

Bachelor's degree in Information Systems, Computer Science, Engineering, Supply Chain, Finance, Accounting, Data Analytics, or a related field, or an equivalent combination of education and relevant experience.
At least 3 years of experience spanning data engineering, ERP systems, inventory or asset management, manufacturing analytics, or data governance.
Demonstrated ability to independently complete assignments of medium scope.
Experience working directly with business users to resolve system and data issues.
Working knowledge of manufacturing operations in an asset-intensive or high-volume production environment.
Hands-on SAP S/4HANA experience in at least one of PM, MM including inventory management, PPPI, or PS; working familiarity across the others; exposure to FSQA; and basic understanding of FICO transactions.
Strong analytical, problem-solving, written, and verbal communication skills.
Ability to identify and trace data discrepancies across processes, system configuration, and master data.
Ability to build effective partnerships across finance, operations, and technology teams.
Willingness and ability to perform the physical requirements of the job, with or without reasonable accommodation.
Resume must be included for consideration.
Must be willing to work on-site; interviews will be conducted on-site.
Approximately 25%–40% travel, depending on assignment.

Nice To Haves

Fiori exposure.
SQL, Python, ETL/ELT tools, and cloud platforms such as Google Cloud Platform or equivalent.
Experience with Power BI, Palantir, Tableau, or Analysis for Excel, in addition to advanced Excel.
Familiarity with data governance platforms such as Collibra or equivalent, including catalogs, lineage, and stewardship concepts.
Exposure to warehouse or storeroom management systems and physical inventory processes.
Food, protein, or other regulated manufacturing experience.
Exposure to SAP S/4HANA implementation, migration, or enhancement work.
Interest in developing toward a senior individual contributor or leadership track.

Responsibilities

Support inventory accounting, valuation, cycle counts, physical inventory adjustments, and identification of slow-moving and obsolete inventory.
Support construction-in-progress controls, capitalization metrics, maintenance and repair analytics, and reconciliation activities.
Design, configure, enhance, and support SAP processes across PM, MM, PPPI, PS, and FSQA, including FICO integration.
Design and maintain data pipelines and interfaces supporting cloud-based reporting and analytics.
Configure and support SaaS solutions for inventory, maintenance, and asset lifecycle management.
Troubleshoot system and data issues and document resolutions clearly.
Maintain master data standards and support data cleansing, harmonization, enrichment, and governance activities.
Develop data quality reporting, documentation, user guides, and training materials.
Translate technical findings into actionable recommendations for business and technology partners.
Support peer development, onboarding, shared standards, and cross-functional improvement initiatives.
Use approved AI tools responsibly, protect sensitive information, follow company policies, validate AI-generated outputs, and apply professional judgment.