Sr. Data & AI Platform Engineer

Altimate Medical•Morton, MN

5d•Hybrid

About The Position

The Sr. Data & AI Platform Engineer will manage and evolve AltimateMedical’s data and AI platforms, including NetSuite and Domo, and guide the company’s data strategy. The role establishes the data foundation, designs platform capabilities and applications, and supports the company’s ability to differentiate itself in the medical technology market. The engineer oversees structured and unstructured data, explores and visualizes data to identify patterns, trends, and anomalies, and applies statistical, machine-learning, and AI-based methods to analyze and model data used in business decisions. This position leads platform and AI projects from planning through delivery, works independently, and partners with cross-functional teams and business leaders. It brings AI and machine learning into production, monitors model performance and drift, and communicates findings through clear visuals and narratives. The role is based in the Minnesota or Chicago area and is in-office or hybrid, with office days negotiable based on proximity to the company’s Minnesota or Illinois locations. Occasional travel to business locations in Frankfort, Illinois; Lenexa, Kansas; and Morton, Minnesota is expected.

Requirements

Master’s degree in Information Management, Data Management, Computer Science, or a related field; an advanced certificate may substitute.
At least 5 years of relevant experience.
Experience with data platforms, ETL frameworks, database systems, data modeling and schemas, and data warehousing.
Working scripting skills in SQL, Python, and/or R to build pipelines and automate platform work.
Use good development practices, such as version control and testing.
Hands-on experience with AI and machine-learning tools.
Ability to work independently and explain technical work in plain language.

Nice To Haves

Experience with Domo or NetSuite.

Responsibilities

Own and evolve data platforms, including NetSuite and Domo.
Manage integrations, ETL pipelines, data models, and data quality across structured and unstructured data.
Lead platform and AI projects from planning through delivery, directing work and partnering with cross-functional teams.
Run AI and machine-learning models in production on the platform and monitor their performance and drift.
Translate complex findings into clear visualizations and narratives for audiences with varied backgrounds.
Shape the data and AI roadmap with IT and business leaders, identifying opportunities for AI and automation.
Explore and analyze data to uncover patterns, trends, and anomalies.