Senior Director, Data Platforms & Governance
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
MiniMed is the only company that commercializes all parts of a connected diabetes ecosystem insulin pumps, CGMs, smart insulin pens, and data software. For over 40 years, we've reimagined what diabetes technology can do, and our data platforms are foundational to that mission. As we scale intelligent insulin delivery systems globally, the integrity, quality, and governance of our data is what makes it all possible. In this highly visible, cross-functional leadership role, the Senior Director, Data Platforms & Governance owns the end-to-end data infrastructure that powers MiniMed's analytics, AI, and product innovation capabilities. You will architect and govern the trusted data foundation on which our most critical clinical, commercial, and operational decisions are made in an FDA-regulated environment where data integrity is not optional. You will lead three pillars: a Data Engineering organization that builds and operates enterprise-grade pipelines and data products; a Databricks Platform team that owns the lakehouse architecture, Unity Catalog governance, and platform reliability; and a Governance & Master Data function that defines the policies, standards, and MDM frameworks that make data trustworthy at scale. This role will directly report to Chief Transformation Officer, and partner with product, engineering, regulatory, and commercial leadership to ensure that MiniMed's data assets are governed, accessible, and fit for AI from Gen AI foundation readiness to FDA audit traceability.
Responsibilities may include the following and other duties may be assigned.
Data Engineering & Platform
- Lead and scale a cross-functional team of data engineers, platform engineers, and data architects delivering end-to-end data solutions across clinical, commercial, supply chain, and operational domains.
- Architect and own the enterprise data hub a unified, governed lakehouse integrating structured and unstructured data from ERP, device telemetry, CRM, and third-party sources serving as the trusted foundation for all analytics, ML, and Gen AI initiatives.
- Own the Databricks platform: Unity Catalog governance, workspace management, Delta Live Tables pipeline orchestration, cluster optimization, and cost governance.
- Define and execute the data platform technology roadmap, evaluating emerging capabilities (e.g., Lakeflow, real-time lakehouse, AI Gateway) and building proof-of-concepts that translate to production delivery.
- Establish and enforce platform reliability standards: SLAs, data quality SLAs, MTTR targets, observability, and incident management.
- Drive year-over-year infrastructure cost optimization through architecture rationalization, compute right-sizing, and vendor consolidation.
Data Governance & Master Data Management
- Define and implement MiniMed's enterprise data governance framework policies, standards, operating models, stewardship roles, and domain ownership structures.
- Own and mature the Master Data Management (MDM) program across critical domains: patient, product, HCP, customer, and device data ensuring consistency, completeness, and lineage across all systems.
- Establish and operate the data governance council; align business domain leads, IT, legal, privacy, regulatory affairs, and quality on data accountability and stewardship.
- Deploy and manage data governance tooling data catalog, lineage tracking, data quality rules engines, metadata management to make governance operational, not theoretical.
- Lead data maturity assessments and build multi-year roadmaps to improve data quality, discoverability, and interoperability across domains.
- Ensure all data practices comply with HIPAA, 21 CFR Part 11, FDA data integrity requirements, and applicable privacy regulations; serve as the data risk owner for audit and regulatory submissions.
AI & Gen AI Data Foundation
- Design and maintain the data foundation layer that enables responsible Gen AI adoption at scale including data quality pipelines, curated feature stores, prompt data repositories, and AI model lineage.
- Partner with the AI Centers of Excellence to ensure governed, high-quality data underpins all Gen AI, predictive, and agentic AI initiatives.
- Define and enforce policies for AI/ML data use, bias prevention, and model traceability in a regulated healthcare context.
Leadership & Organizational Development
- Build, lead, and develop a high-performing, inclusive team; establish coaching, mentoring, and career development programs that grow technical depth and leadership capacity.
- Manage a multi-million-dollar platform and engineering budget; drive cost efficiency while scaling capability.
- Act as a trusted advisor to executive leadership on data strategy, platform investments, and data risk translating complex technical tradeoffs into clear business decisions.
- Represent data platform and governance in cross-functional program governance forums, ensuring data initiatives are captured in the transformation roadmap and funded appropriately.
Required Knowledge and Experience:
Requires a Bachelors degree and minimum of 15 years of relevant experience with 10+ years of managerial experience, or advanced degree with a minimum 13 years prior relevant experience, minimum of 10 years of managerial experience.
Preferred Qualifications:
- Advanced degree (MS, MBA, or equivalent)
- 15+ years of progressive experience in data engineering, data platform architecture, and data governance, with at least 10 years in a people leadership role
- Proven track record building and leading large, cross-functional data engineering organizations (50+ engineers) in a regulated or complex enterprise environment
- Deep, hands-on expertise with cloud-native data platforms specifically Databricks (Unity Catalog, Delta Live Tables, MLflow, Lakeflow), 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)
- Experience defining and operationalizing enterprise data governance frameworks, MDM programs, and data stewardship operating models at scale
- 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
- Experience working in FDA-regulated, HIPAA-covered, or equivalent highly regulated environments; understanding of 21 CFR Part 11 data integrity requirements
- Experience in medical device, digital health, or life sciences industries
- Demonstrated success unlocking measurable business impact ($50M+) through data platform and analytics programs
- Hands-on experience with Gen AI data foundation design prompt data pipelines, vector stores, retrieval-augmented generation (RAG) data layers, and AI model lineage
- Databricks certifications: Data Engineer Professional, Lakehouse Fundamentals, or equivalent
- Experience with Six Sigma, Lean, or continuous improvement frameworks applied to data operations (MTTR reduction, SLA improvement, cost optimization)
- Knowledge of data product thinking designing data as a product with defined consumers, SLAs, and ownership
- Familiarity with Unity Catalog AI Gateway, real-time lakehouse patterns, or Databricks Lakeflow for agentic data workflows
- CDMP, DAMA, or equivalent data management certification
- Experience building and running an Analytics or Data Center of Excellence (CoE)
- Proficiency in Python, PySpark, Scala, or SQL for technical fluency and architecture review
- Microsoft Certified Azure Architect or equivalent cloud certification
