Sr Engineer Logistics Data

Tyson Foods, Inc. has an opening for Senior Engineer Logistics Data in Springdale, AR. Architect scalable data solutions, including data warehousing and big data technologies, and ensure alignment with organizational goals. Partner with key stakeholders to design and implement data architecture solutions for Tyson Private Fleet, coordinating integration efforts with third-party vendors (10% of the time). Lead the development of data visualization strategies, ensuring they contribute to data-driven decision-making at a strategic level. Collaborate with business stakeholders to identify key data visualization needs and priorities, guiding the development of impactful Power BI reports (22% of time). Lead the design and orchestration of complex data pipelines and ETL processes, focusing on optimizing data models. Collaborate with IT developers to design and implement data ingestion solutions for the Tyson data lake, including creating entity relationship diagrams (ERDs), developing ETL codes, and performing data transformation and cleansing to optimize data quality and usability (25% of time). Implement advanced data governance frameworks and ensure robust data security measures. Optimize cloud costs by strategically using cloud resources and efficient data architectures. Design and deploy enterprise-scale data visualization solutions, optimizing performance within tools. Interact with 3rd party vendors to incorporate new functionality and evaluate tools (16% of time). Resolve complex escalations and situations, driving effective resolutions. Ensure adherence to data privacy and security practices to protect sensitive information (12% of the time). Communicate effectively with stakeholders to understand and address their needs through data visualization. Conduct weekly meetings with stakeholders from Tyson Private Fleet, Transportation Safety, and Transportation Operations to discuss current and upcoming projects, ensuring their data visualization needs are understood and addressed effectively. Lead efforts to automate reporting processes to improve efficiency and accuracy (10% of time). Mentor and support junior engineers and interns in report creation, contributing to data-driven decision-making at the operational level, including SQL, scripting, and advanced data visualization techniques, ensuring the creation of intuitive and visually appealing dashboards (5% of time).

Job requirements:

Requires a Bachelor's degree or foreign equivalent degree in Applied Business Analytics, Logistics, Data Science, or a related field, and three (3) years of experience in the position offered or related role, including experience with developing, optimizing, and maintaining enterprise‑level reporting and analytics solutions using Power BI, or Tableau.

Experience must include one (1) year of experience in each of the following:

• Supporting enterprise business intelligence environments on Google BigQuery and Microsoft SQL Server.
• Writing and optimizing complex SQL queries and data models using SQL Server Management Studio, Google BigQuery.
• Designing and delivering automated dashboards and data visualizations to support business decision‑making using advanced visualization platforms like Power BI and Tableau.
• Designing, maintaining, and querying relational databases using SQL Server Management Studio and Google BigQuery.
• Supporting large software implementations by coordinating with cross-functional stakeholders to gather and document data requirements, define desired outcomes, and translate business needs into enterprise-standard data models and data visualization solutions to measure implementation success and support ongoing operations.

Please submit your application online through this site. All professional team members are expected to demonstrate responsible use of approved AI tools, including safeguarding sensitive information, adhering to company policies, and validating AI-generated outputs. Individual Contributors should demonstrate the ability to integrate AI into daily work, improve efficiency through AI-enabled solutions, evaluate outputs critically, and apply professional judgment when using AI. People Leaders should demonstrate the ability to drive responsible AI adoption, enable effective use of approved solutions, identify opportunities to improve team performance through AI, and ensure accountability for the quality and accuracy of AI-supported outcomes.