We anticipate the application window for this opening will close on - 30 Oct 2026At MiniMed, you can begin a lifelong career of exploration and innovation, while helping make a difference in the lives of people living with diabetes around the globe. You'll lead with purpose, breaking down barriers to innovation for a more connected, compassionate world.
About the Role
As the Senior Manager, Data Platforms & Governance, you will lead the tactical execution and day-to-day operations of the data solutions, powering our analytics, AI, and product innovation.
Reporting directly to the Senior Director, Data Platforms & Governance, you will manage engineering teams responsible for maintaining a trusted, FDA-compliant data foundation. In addition to core data governance, you will directly oversee the architecture modernization efforts, including end-to-end solution design, Medallion Lakehouse implementation, and the migration of enterprise reporting from Snowflake to Databricks.
This role is Hybrid requiring 3 days minimum on-site per week.
Responsibilities may include the following and other duties may be assigned.
Migration, Architecture & Solution Design
- Lead the Power BI reporting migration from Snowflake to Databricks, ensuring zero business disruption and seamless continuity for analytical dashboards.
- Manage end-to-end solution design incorporating complex data integration pipelines, scalable backend engineering, and front-end enterprise reporting.
- Own the Medallion Architecture implementation (Bronze, Silver, Gold layers) within Databricks to systematically clean, enrich, and structure data for production readiness.
- Design complex data workflows and highly available distributed systems that seamlessly merge clinical telemetry, ERP, and CRM data streams.
- Enforce robust data model design principles , optimizing star/snowflake schemas, aggregate tables, and semantic layers for analytical speed.
- Optimize workloads and compute performance across both migration phases and steady-state processing to lower cloud consumption costs and query latency.
Data Engineering Execution
- Manage and mentor a team of data engineers, platform engineers, and data architects delivering end-to-end data pipelines.
- Implement reliability standards , tracking operational SLAs, data quality metrics, and driving MTTR reduction.
Data Governance & Master Data Management (MDM)
- Operationalize policies and standards defined by MiniMed's enterprise data governance framework.
- Supervise data stewards to ensure data consistency, lineage, and completeness across patient, product, and device domains.
- Enforce compliance standards including HIPAA, 21 CFR Part 11, and FDA data integrity requirements across all managed pipelines.
- Support regulatory audits by preparing technical data lineage documentation and quality compliance logs.
AI & Gen AI Foundation Support
- Deploy data pipelines optimized for Gen AI adoption, including curated feature stores and vector-store repositories.
- Track model lineage and maintain data traceability to prevent bias within a regulated medical context.
Team Leadership & Administration
- Drive team performance through routine coaching, performance reviews, and technical skill development.
- Monitor operational spend , identifying cost efficiencies within the allocated platform infrastructure budget.
- Provide technical updates to the Senior Director to assist in roadmap planning and risk assessment.
Required Knowledge and Experience:
To be considered for this role, please ensure the minimum requirements are evident on your resume.
Requires a Bachelor's degree and minimum of 7 years of relevant experience with 5+ years of managerial experience, or advanced degree with a minimum of 5 years of relevant experience with 5+ years of managerial experience.
Preferred Qualifications:
- Progressive experience in data engineering, data hub architecture, and data governance, with at least 3 years in a people leadership role
- Deep, hands‑on expertise with cloud‑native data platforms - like Databricks/Snowflake and cloud infrastructure on AWS or Azure (ADLS, ADF, S3, Glue)
- Demonstrated experience designing and delivering enterprise data hubs or lakehouse architectures integrating multi‑source data (ERP/SAP, IoT/device, CRM, third‑party feeds)
- Proficiency in Python, PySpark, Scala, or SQL for technical fluency and architecture review
- Proven track record of successfully migrating large‑scale enterprise data footprints from Snowflake to Databricks without reporting downtime.
- Architectural Mastery: Advanced expertise in designing Medallion architecture frameworks, data model design and deploying automated pipeline orchestrations.
- Coding Fluency: Strong operational proficiency in SQL, Python, or PySpark for reviewing code and complex system architectures.
- Familiarity with data governance and quality tooling (data catalogs, lineage tools, MDM platforms, data quality engines)
- Strong business acumen: ability to frame dat