Logistics Data Engineer (Corporate 412 West)

Tyson Foods, Inc.•Springdale, AR

1d•Onsite

About The Position

The Data Engineer is responsible for developing and supporting scalable data solutions that enable operational reporting, analytics, automation, and business decision-making. This role contributes to the design and maintenance of data pipelines, data models, and visualization solutions that improve visibility into warehousing and logistics operations. Data Engineers work closely with analysts, business stakeholders, and IT teams to deliver reliable, business-facing solutions that drive efficiency, visibility, and process improvement. This role also supports the team’s continued evolution toward advanced analytics, intelligent automation, and AI-enabled capabilities through strong data engineering fundamentals and a willingness to learn emerging technologies.

Requirements

1+ years of relevant or practical experience in data engineering, analytics, reporting, or related technical fields.
Proficiency in SQL, data transformation, and reporting or visualization tools.
Understanding of data warehousing concepts and foundational data architecture principles.
Familiarity with ETL/ELT processes, data pipeline orchestration, and monitoring concepts.
Ability to work with structured and semi-structured data sources.
Initiative: Proactively identifying opportunities for process improvement and automation.
Teamwork: Collaborating effectively with analysts, business stakeholders, IT teams, and cross-functional partners.
Communication: Explaining technical concepts and data insights to non-technical audiences.
Critical Thinking: Analyzing business and data challenges to recommend practical solutions.
Adaptability: Quickly learning and applying new tools, technologies, and processes.
Time Management: Managing multiple priorities and delivering high-quality work in a fast-paced environment.
Attention to Detail: Ensuring data accuracy, consistency, and reliability across solutions.

Nice To Haves

Exposure to cloud-based data environments and big data technologies is a plus.
Interest in automation, advanced analytics, or AI-enabled data solutions.
Experience or familiarity with supply chain, logistics, or warehouse operations is preferred.

Responsibilities

Collaborate with analysts and business stakeholders to understand operational requirements and deliver effective data solutions.
Design, build, and support reporting datasets, dashboards, and visualization solutions that improve operational and strategic decision-making.
Write and optimize SQL queries, calculations, and data transformations to improve data quality, performance, and usability.
Design, implement, and maintain data pipelines with a focus on reliability, scalability, and monitoring.
Develop and support ETL/ELT processes and contribute to data warehousing solutions, including dimensional modeling concepts such as star schema methodologies.
Assist in building data foundations that support automation, predictive analytics, and advanced reporting use cases.
Identify opportunities to improve or automate manual data and reporting processes.
Support data governance initiatives and ensure compliance with data security and access standards.
Participate in cloud and compute optimization efforts through efficient data design and resource usage.
Contribute to data architecture discussions and support real-time or near real-time data processing initiatives.
Build strong business relationships by learning operational processes, systems, terminology, and reporting needs within warehousing and logistics.
Collaborate with IT teams to support scalable and secure production solutions.
Perform other assigned job-related duties aligned with organizational goals and team objectives.