Sr Director, Enterprise Data

Waters Corporation•Milford, MA

About The Position

Waters is seeking a Senior Director, Data & Analytics to define and lead the enterprise data and analytics strategy that enables insight‑driven decision making, operational excellence, and scalable digital transformation across the organization. This role is responsible for data strategy, analytics platforms, data engineering, master data management, and AI‑enabled analytics, and for building and leading a high‑performing, cross‑functional team that partners closely with business and IT leaders to embed data, analytics, and AI into how Waters operates. Waters in going through a major integration to two business from BD and this leader will be the key leader for defining the data strategy for the IT and business integration.

Requirements

15+ years of experience across data, analytics, information management, and technology leadership.
Proven experience defining and executing enterprise data, analytics, AI, and master data strategies.
Demonstrated ability to lead cross‑functional, global teams and influence senior executive stakeholders.
Experience delivering executive‑level analytics and driving adoption at scale.
Enterprise data, analytics, and AI strategy
Master data management and data governance
Data architecture and data engineering
Advanced analytics and AI‑enabled decision support
Executive communication and influence
Change management and organizational adoption
Agile / Scrum leadership and delivery

Nice To Haves

Master’s degree in Computer Science, Engineering, Data Science, or a related discipline preferred.

Responsibilities

Enterprise Data, Analytics & AI Strategy
Define and drive Waters’ enterprise data, analytics, and AI strategy, including data architecture, analytics platforms, and operating model.
Establish a clear roadmap for how analytics and AI capabilities are used to improve business performance, decision quality, and speed to action. Build business cases to drive and track performance of all data initiatives.
Partner with senior leaders to identify and prioritize high‑value AI and advanced analytics use cases, ensuring alignment to enterprise strategy and measurable business outcomes.
Ensure analytics and AI initiatives are designed as enterprise capabilities, not point solutions, and can be scaled and reused across functions.
AI & Advanced Analytics Enablement
Lead the responsible adoption and operationalization of AI‑enabled analytics, including predictive, prescriptive, and generative analytics use cases.
Ensure that AI solutions are built on trusted, well‑governed, and AI‑ready data, and are embedded into business workflows rather than isolated tools.
Partner closely with IT, security, legal, and compliance teams to ensure the ethical, secure, and compliant use of AI, including appropriate controls, transparency, and risk management.
Drive organizational readiness for AI by promoting data and AI literacy, helping leaders and teams understand where AI adds value and where human judgment remains essential.
Track and communicate the business impact of AI and advanced analytics initiatives, linking insights to actions and outcomes.
Analytics & Business Insights Enablement
Lead the design, implementation, and adoption of enterprise analytics solutions, including executive‑level dashboards and performance management analytics.
Enable efficient identification of business performance gaps, accelerate root‑cause analysis, and support tracking of actions to address underperformance.
Partner with business leaders to ensure analytics solutions are decision‑oriented, actionable, and trusted, rather than purely descriptive.
Master Data Management & Data Governance
Establish and lead Waters’ master data management (MDM) strategy in partnership with the Transformation Office, ensuring consistent, accurate, and authoritative master data across critical domains (e.g., customer, product, supplier, financial, and operational data).
Define platform programs to enable ownership, stewardship, and accountability models for master and reference data in partnership with business and IT stakeholders.
Drive the implementation of enterprise data governance platforms including data quality standards, metadata management, and data lifecycle management.
Data Platforms, Architecture & Engineering
Own the enterprise data and analytics architecture, including data engineering, integration, and analytics platforms.
Define standards and patterns for data ingestion, transformation, and consumption to support analytics, AI, and reporting needs.
Ensure platforms and architectures are scalable, secure, and aligned with enterprise technology standards and roadmaps.
Team Leadership & Operating Model
Build, lead, and develop a cross‑functional data and analytics organization with capabilities spanning data engineering, analytics, data science, visualization, MDM, and governance.
Establish clear engagement models between central data & analytics teams and domain‑specific partners.
Foster a culture of accountability, continuous improvement, and strong business partnership.