Senior Manager - Data Analytics and Governance

MiniMed•Johns Creek, GA

3d•$136,000 - $230,000•Hybrid

About The Position

At 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.

Requirements

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.
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.
Advanced expertise in designing Medallion architecture frameworks, data model design and deploying automated pipeline orchestrations.
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 data platform strategy in terms of business value, quantify outcomes, and influence executive-level decisions
Prior background working in medical devices, digital health, life sciences, or a HIPAA-covered environment.
Cloud Data Technology platform certifications: Data Engineer Professional, Lakehouse Fundamentals, or equivalent
Experience with continuous improvement frameworks applied to data operations (MTTR reduction, SLA improvement, cost optimization)
CDMP, DAMA, or equivalent data management certification

Responsibilities

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.
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.
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.
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.
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.