Senior Principal Enterprise Data Architect, Process Mining & Commercial Data

Waters Corporation•Milford, MA

About The Position

The Senior Principal Enterprise Data Architect defines and implements enterprise data architecture that enables commercial excellence, process mining, AI, automation, and advanced analytics across the organization. The role establishes trusted, scalable, AI-ready data foundations across Salesforce, SAP, Marketo, Celonis, Power BI, and related business platforms, while improving data quality, governance, and business process performance. The architect leads commercial data quality, governance, and Master Data Management strategies; serves as the Celonis architecture subject matter expert; and designs secure, scalable, auditable data solutions and Python- and SQL-based pipelines. The role also sets standards for data engineering, integration, CI/CD, and MLOps, and partners with cross-functional business and technical stakeholders to identify process optimization and automation opportunities.

Requirements

12+ years of experience in enterprise data architecture, data engineering, process mining, AI platforms, MLOps, or related technical disciplines.
Deep expertise in Celonis, including process mining, data modeling, transformations, and Action Flows.
Strong hands-on experience with Salesforce, Python, and SQL within large-scale commercial data environments.
Demonstrated experience designing and implementing enterprise data governance, data quality, and Master Data Management frameworks.
Experience defining architecture standards and operating models for data, analytics, AI, and automation platforms.
Knowledge of cloud technologies and distributed data architectures.
Experience integrating complex commercial systems, including CRM, ERP, marketing automation, and business intelligence platforms.
Strong problem-solving skills and a track record of delivering scalable data solutions in complex, global organizations.
Excellent communication and stakeholder management skills, with the ability to influence technical and business audiences.
Experience with process automation, orchestration tools, and modern DevOps/MLOps practices.
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.

Nice To Haves

Experience with Microsoft Azure environments.
Master’s degree.
Experience architecting commercial data platforms supporting global sales, marketing, service, and operations teams.
Expertise in AI and machine learning platform enablement, including production-ready data and model lifecycle management.
Experience driving process improvement initiatives through Celonis process intelligence and automation capabilities.
Background working in highly regulated, global, or enterprise-scale environments.

Responsibilities

Define and implement enterprise data architecture supporting commercial analytics, process mining, AI, automation, and digital transformation initiatives.
Lead commercial data quality, governance, and Master Data Management strategies across Salesforce, SAP, Marketo, Celonis, Power BI, and other business-critical platforms.
Serve as the subject matter expert for Celonis architecture, including data models, transformations, process mining capabilities, and Action Flows.
Establish data quality standards, monitoring frameworks, and validation processes to improve data integrity and business outcomes.
Design and govern scalable, secure, and auditable data solutions for enterprise AI, automation, and predictive analytics initiatives.
Define standards and best practices for data engineering, integration frameworks, CI/CD, and MLOps across commercial data environments.
Lead the design and development of Python- and SQL-based data pipelines integrating commercial systems and enabling advanced analytics.
Partner with business and technical stakeholders to identify opportunities for process optimization, automation, and operational excellence through process mining.
Drive continuous improvement through greater visibility into commercial processes, data performance, and workflow automation.
Provide technical guidance and architectural expertise to cross-functional teams spanning data engineering, analytics, and AI initiatives.