Senior Data Engineer - Corporate Office (Austin, MN preferred

Austin, MN, United States and 1 more

SENIOR DATA ENGINEER – CORPORATE OFFICE (AUSTIN, MN PREFERRED)

HORMEL FOODS CORPORATION

To save time applying, Hormel Foods does not offer sponsorship of job applicants for employment-based visas for this position at this time.

ABOUT HORMEL FOODS

Hormel Foods Corporation, based in Austin, Minnesota, is a global branded food company with approximately $12 billion in annual revenue across more than 80 countries worldwide. Its brands include

Planters ® , Skippy ® , SPAM ® , Hormel ® Natural Choice ® , Applegate ® , Wholly ® , Hormel ® Black Label ® , Columbus ® , Jennie-O® and more than 30 other beloved brands. The company is a member of the S&P 500 Index and the S&P 500 Dividend Aristocrats, was named one of the best companies to work for by U.S. News & World Report, one of America’s most responsible companies by Newsweek, recognized by TIME magazine as one of the World’s Best Companies, and has received numerous other awards and accolades for its corporate responsibility and community service efforts.

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As a Senior Data Engineer, you will lead the Supply Chain Data Engineering team responsible for delivering curated data assets, data pipelines, dimensional models, semantic models, and foundational data capabilities that support planning, procurement, manufacturing, inventory, logistics, and transportation across Hormel Foods.

This role plays a key part in advancing our Enterprise Data Foundation by leveraging technologies Google Cloud Platform (GCP), Big Query, Composer (Airflow), enterprise Python-based ingestion and orchestration capabilities, Incorta, and enterprise semantic layer technologies. This role will help bridge Hormel’s modern cloud data ecosystem and legacy enterprise data platforms while delivering trusted data assets that power Supply Chain analytics and decision-making.

• Lead and develop the Supply Chain Data Engineering team responsible for delivering curated data assets, data pipelines, dimensional models, semantic models, and foundational data capabilities supporting planning, procurement, manufacturing, inventory, logistics, and transportation. Utilize enterprise ingestion, orchestration, and platform capabilities to acquire, integrate, transform, and curate data that supports analytics, reporting, and business decision-making.
• Partner with Supply Chain stakeholders, Data Products & Solutions teams, architects, data scientists, and application teams to prioritize initiatives and deliver scalable data solutions that support business objectives.
• Design, develop, and support Supply Chain data solutions across modern and legacy platforms, including Big Query, Composer (Airflow), Python, Incorta, Oracle Analytics Server (OAS), Oracle Enterprise Data Warehouse, Informatica, PL/SQL, and enterprise semantic layer technologies.
• Establish and promote engineering best practices, including data modeling standards, code reviews, testing strategies, CI/CD adoption, monitoring, observability, and operational support processes.
• Partner with Data Governance teams and business data stewards to implement and maintain data quality rules, metadata cataloging, business glossary definitions, critical data elements, observability capabilities, and data remediation processes across Supply Chain data domains.
• Drive modernization initiatives that advance the Enterprise Data Foundation, improving scalability, reliability, developer productivity, and long-term maintainability while reducing technical debt.
• Provide technical leadership through architecture reviews, design reviews, mentoring, coaching, and cross-functional collaboration with Data Platform Engineering, Architecture, Infrastructure, Security, Governance, and Integration teams.

• Bachelor’s degree in computer science, MIS, engineering, mathematics, or related field, and significant experience supporting enterprise data, analytics, and technology platforms.
• 7+ years of experience developing and optimizing SQL solutions.
• 7+ years of experience designing, implementing, and supporting enterprise data warehouse, lakehouse, or modern data…