Data Engineer: AI & ML Data Foundations (Onsite, CO)

Medtronic; Lafayette (CO); On-site; USD 89,000 - 133,000; Full time

Benefits offered by this job

Competitive salary

Health, dental, and vision insurance

401(k) with employer match

Tuition assistance

Job summary

Medtronic CST is seeking a Data Engineer to build and manage data foundations for advanced algorithms and AI/ML development across surgical planning, navigation, and robotics programs. You will lead data acquisition, annotation operations, and governance while partnering with cross-functional teams.

The role emphasizes data reliability, scalability, and compliance, with opportunities to influence research and product development decisions through data-driven analytics.

Qualifications

• Bachelor’s degree or higher with relevant data-engineering experience.
• Experience handling large-scale datasets in academic or industry settings.
• Proficiency with Python or SQL for data manipulation.
• Ability to integrate data from multiple sources for AI/ML needs.
• Experience with AI tools in professional/academic contexts.

Responsibilities

• Lead data acquisition, curation, and preparation for R&D and product development.
• Coordinate data collection workflows across clinical, lab, and external sources.
• Manage internal/external annotation programs to deliver high-quality labeled datasets.
• Partner with researchers and engineers to define data requirements for AI/ML initiatives.
• Ensure data quality, governance, and compliance across datasets.

Skills

Data acquisition

Data annotation

AI/ML data

Python/SQL

Data governance

Data quality

Education

Bachelor’s degree

Master’s degree

Tools

AWS

Snowflake

Cloud infrastructure

Job description

Medtronic CST is seeking a Data Engineer to build and manage data foundations for advanced algorithms and AI/ML development across surgical planning, navigation, and robotics programs. You will lead data acquisition, annotation operations, and governance while partnering with cross-functional teams.

The role emphasizes data reliability, scalability, and compliance, with opportunities to influence research and product development decisions through data-driven analytics.