Data & AI Engineer

Winnebago Industries•Eden Prairie, MN

1d•Hybrid

About The Position

The Data & AI Engineer supports enterprise Artificial Intelligence (AI), Data Integration (DI), Business Intelligence (BI), and Master Data Management (MDM) initiatives across Winnebago Industries. This role designs, builds, and supports data pipelines, AI solutions, and analytics capabilities that enable trusted, data-driven decision making. The engineer partners with business and technical stakeholders to implement data governance standards, manage master data, and operationalize AI and machine learning solutions. Working collaboratively with project teams and service partners, the role delivers scalable, secure, and reliable data and AI solutions that drive measurable business value and support enterprise priorities.

Requirements

3+ years of experience with Spark (PySpark/SQL) and Delta Lake engineering skills.
Proven experience designing, implementing, and maintaining data and analytics capabilities using Microsoft Azure, Databricks, Python or comparable technologies.

Responsibilities

Design, build, and optimize scalable data pipelines and AI solutions using Azure and Databricks to help drive platform strategy/roadmaps.
Develop and operationalize LLM/ML/AI capabilities into pipelines and workflows that continuously improve output quality and performance as use cases evolve.
Implement and maintain enterprise ontology, master data management, data standards, and data quality practices to enable analytics and AI solutions.
Leverage Dev/Sec/Ops best practices, including CI/CD, automated testing, and automation to increase delivery speed and operational stability.
Partner with development and data teams across the organization, fostering a culture of best practices, innovation, and continuous improvement.
Support and operate existing / legacy data platforms and integrations.
Collaborate with business and analytics teams to translate requirements into technical designs that deliver measurable business value.
Other duties as assigned based on business need.