Senior Data Engineer – Warehousing Analytics

Tyson Foods, Inc.•Springdale, AR

23h

About The Position

The Senior Data Engineer is a technical leader responsible for designing and building scalable data solutions, including real-time data pipelines, data models, and advanced data architectures that support operational and strategic decision-making. This role requires strong expertise in data engineering fundamentals such as data streaming, pipeline orchestration, and performance optimization, while also ensuring cost efficiency and data security across systems. In addition to core engineering responsibilities, this role partners closely with business stakeholders and IT to deliver production-ready, business-facing data solutions. The Senior Data Engineer will play a key role in evolving the team’s capabilities toward AI-driven insights and automation, enabling more intelligent and proactive decision-making across warehousing and logistics operations.

Requirements

Bachelor’s or Master’s degree in Business, Analytics, Data Science, Supply Chain Management, or a related field preferred. Equivalent experience may be considered.
3+ years of relevant experience in data engineering, analytics engineering, or related fields, with demonstrated experience delivering end-to-end data solutions in a business-facing environment.
Strong experience with data pipeline development, data modeling, and scalable data architecture.
Understanding of data security, governance, and access control best practices.
Ability to work with structured, semi-structured, and unstructured data to support advanced analytics use cases.
Experience building data products, tools, or workflows that directly support business operations.
Ability to work directly with operations teams to understand needs and deliver practical solutions (Business Partnership).
Takes initiative to identify opportunities and drive solutions from concept to implementation (Ownership).
Comfortable working in ambiguous environments and translating business problems into technical solutions (Problem-Solving).
Bridges the gap between business stakeholders, analytics teams, and IT (Communication).
Eagerness to learn and apply new technologies, particularly in AI and automation (Adaptability).
Guides and develops junior team members (Mentorship).

Nice To Haves

Master’s degree in Business, Analytics, Data Science, Supply Chain Management, or a related field.
Experience with real-time or near real-time data processing.
Exposure to or interest in AI/ML concepts, data preparation for modeling, or intelligent automation workflows.
Experience or familiarity with supply chain, logistics, or warehouse operations.

Responsibilities

Architect scalable data solutions, including data warehousing and real-time data processing, aligned with business and operational goals.
Lead the design and orchestration of complex data pipelines and ETL/ELT processes, optimizing for performance, scalability, and reliability.
Build and support data foundations that enable advanced analytics, predictive insights, and automation use cases.
Collaborate with analysts and business stakeholders to develop and operationalize advanced analytics solutions, ensuring data is structured and accessible for modeling and decision-making.
Identify and implement opportunities to automate manual business processes through data workflows and intelligent solutions.
Work closely with warehousing and logistics teams to translate operational challenges into scalable data solutions.
Develop data products that improve visibility into service, inventory, labor, and operational performance.
Collaborate with IT teams to align on architecture, security, and data standards while maintaining ownership of business-facing analytics solutions.
Implement data governance frameworks and ensure secure handling of sensitive data, including row-level and column-level security.
Optimize cloud and compute usage through efficient data design and resource management.
Collaborate with analysts and business stakeholders to design and maintain scalable data models that enable reporting and dashboards used for operational and strategic decision-making.
Lead complex initiatives, mentor team members, and drive best practices in data engineering and solution design.
Communicate effectively with technical and non-technical stakeholders to deliver impactful solutions.
Perform other assigned job-related duties aligned with organizational goals and team objectives.