Overview As Director of Data Platform Engineering, you own Waters' Enterprise Data Platform end-to-end-from architecture to governance and cost efficiency. You lead a direct platform engineering team and a matrixed GCC, aligning delivery with Waters' data and AI strategy. You partner with data engineering, analytics, and data science to ensure reliable, scalable platforms that enable business outcomes. This role offers high impact across global teams and regulated environments, with a clear path to shaping the company's data ecosystem.
Responsibilities- Design and own the end-to-end architecture of the Enterprise Data Platform (Databricks Lakehouse, Power BI semantic layer, SAP touchpoints)
- Lead Infrastructure as Code efforts in Terraform (workspaces, Unity Catalog, compute policies, CI/CD pipelines)
- Enforce Unity Catalog governance (permissions, data classification, lineage, security, audit controls)
- Shape Delta Lake architecture, cluster optimization, job orchestration, and observability across environments
- Partner with data engineering, analytics, and data science to ensure stable and right-sized compute for workloads
- Build and govern a high-performance Power BI enterprise environment (semantic models, deployment pipelines, workspace governance, RLS)
- Bridge Databricks Lakehouse and Power BI consumption layers for reliable, self-service analytics
- Define BI engineering standards (DAX practices, incremental refresh, dataflow architecture)
- Evaluate and support AI/ML platform capabilities aligned with Waters' Data and AI strategy (model lifecycle, feature engineering, registry, vector search)
- Maintain AI-readiness of the data estate (quality, lineage, access controls) and govern AI workloads for security and compliance
- Lead Platform Operations as a formal discipline (runbooks, SLAs/SLOs, observability, incident response)
- Own on-call and incident management, change management for platform configuration and governance
- Direct and GCC leadership: set priorities, governance, and onboarding; ensure cross-time-zone collaboration
- Drive data governance, security, compliance (Unity Catalog, data classification, lineage, audit controls; GxP/21 CFR Part 11 awareness)
- Partner with business stakeholders to translate priorities into platform roadmaps; own total cost of ownership and cloud spend accountability
- Engage vendors (Databricks, Microsoft/Azure, SAP) to leverage platform capabilities
- Represent platform engineering in architecture reviews and risk discussions
Key requirements- 10+ years in data platform engineering or data architecture
- 5+ years in senior or lead role with direct team responsibility
- Deep Databricks expertise (Unity Catalog, workspace administration, Delta Lake, Lakehouse)
- Enterprise-scale Power BI experience (semantic models, deployment pipelines, RLS)
- Strong IaC experience with Terraform (CI/CD integration, state management, modules)
- Experience leading direct and GCC/distributed teams
- Cloud platform experience (Azure or AWS), IAM, networking, security patterns
- Strong communication with senior leadership; able to balance engineering depth with business context
- Working knowledge of AI/ML platform patterns and MLOps (model lifecycle, pipelines, monitoring)
- strong communication
- cross-functional collaboration
- leadership and people development
- Databricks Lakehouse
- Unity Catalog
- Delta Lake
