Job Summary
Medtronic is a global leader in healthcare technology focused on alleviating pain, restoring health, and extending life. As a Supply Chain Master Data Analyst – Logistics, you will ensure the accuracy and integrity of logistics data across transportation, warehousing, and trade operations. Partnering with supply chain, IT, and data architecture teams, you’ll drive process improvements, support strategic analysis, enhance data quality, and help enable data-driven decisions across Medtronic global operations.
Job Description
Medtronic is a global healthcare technology leader whose mission is to alleviate pain, restore health, and extend life, and the Supply Chain Master Data Analyst Logistics plays a key role in enabling accurate, data-driven decisions across its operations. In this role, you will focus on the integrity and quality of logistics master data used for transportation, warehousing, and trade, supporting critical business processes and global collaboration.
Responsibilities:
- Analyze and maintain high standards of logistics master data accuracy.
- Collaborate with supply chain and IT teams to resolve data integrity issues.
- Identify and implement process improvements that enhance data quality.
- Support strategic supply chain analysis using curated master data sets.
- Participate in cross-functional projects as a key user for logistics data systems.
- Conduct quality assurance testing on data analytics and system enhancements.
Requirements:
- Bachelor’s degree in a relevant field, preferably Computer Science.
- Minimum of four years of experience in data analytics or equivalent.
- Proven experience with data profiling, data quality, and data governance.
- Familiarity with ERP, PLM, and BI tools such as Snowflake, PowerBI, and SAP.
- Strong SQL skills and ability to translate business needs into data models.
- Ability to work independently and collaborate effectively with remote teams.
Benefits:
- Competitive salary and flexible benefits package.
- Opportunities to support a mission-driven, global organization.
- Exposure to diverse teams, systems, and geographies.
This role offers the chance to shape data foundations that support life-saving technologies around the world.