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As Senior Director of Enterprise Data & Governance, you will lead a critical function within the Data Office, partnering directly with business units across the organization. You will be responsible for optimal data modeling, data architecture urbanization, and transforming the data ecosystem into a governed, scalable, AI-ready asset.
You will manage a cross-functional team of data analysts organized into agile pods, overseeing their delivery of data models, pipeline management, and analyses that drive operational optimization across Sales, Marketing, Finance, Procurement, Legal, HR, and Operations. You will work closely with C-suite and VP-level leadership to develop and execute enterprise data strategy aligned with business objectives.
Key responsibilities include: directing data pod teams and fostering a culture of performance and continuous learning; developing data roadmaps compatible with ERP systems, planning tools, and billing engines; designing and executing a Master Data Management (MDM) strategy to establish a single source of truth across operational systems and financial infrastructure; establishing data governance policies, standards, and procedures; enforcing data quality standards and integrity across the organization; ensuring regulatory compliance across global data footprint; and modernizing data consumption models from static dashboards to dynamic semantic layers and GenAI-driven solutions.
You will partner with the Data Solutions team managing data warehouses, collaborate with analytical engineers and business partners on complex requirements, and drive adoption of rigorous analytical standards and methodologies. Your expertise in SaaS data lifecycle management (CRM, ERP, billing engines, semantic consumption layers) will be essential to transforming the operational model and supporting growth.
Required: 15+ years in data operations, MDM, or data architecture, with at least 7 years in executive or senior director-level roles. Strong technical mastery of data architecture, MDM design, and governance frameworks. Proven experience leading distributed, cross-functional data teams. Deep knowledge of enterprise data systems, financial ERP integration, and data quality management. Experience with modern data stack tools and GenAI applications.
