Senior AI Data Architect Director

Presidio, Where Teamwork and Innovation Shape the Future

At Presidio, we're at the forefront of a global technology revolution, transforming industries through cutting-edge digital solutions and next-generation AI. We empower businesses - and their internal customers - to achieve more through innovation, automation, and intelligent insights.

The Senior AI Data Architect Director is a senior, strategy-driven role responsible for designing and evolving the enterprise semantic model that underpins analytics and AI across Presidio. This person sets the architectural direction for how business data is modeled, governed, described, and surfaced, ensuring a single, trusted definition of our metrics and a consistent, AI-ready foundation that both people and AI agents can rely on.

Working at the intersection of the BI and Analytics team, Revenue Operations, Finance, and the AI Enablement function, the AI Data Architect translates business needs into a durable, domain-oriented data architecture spanning Microsoft Fabric, Microsoft Azure, Data Visualization Platforms (e.g., PBI, Tableau), and Salesforce (SFDC). The role pairs strong enterprise data architecture expertise with strong cross-functional partnership and a clear point of view on data governance, semantic standards, and AI enablement.

This person works in close partnership with existing data platform leadership to build a deep command of the current Microsoft Fabric and Azure environment and accelerate trusted AI enablement across the enterprise.

• Lead the evolution of the strategy and roadmap for the enterprise AI semantic model architecture, defining how core business entities, metrics, and relationships are modeled for consistent reuse across analytics and AI.
• Design the semantic model to expose governed, well-described data and metric definitions in close partnership with the BI & Analytics Team and cross functional stakeholders into BI tools, AI agents, and downstream consumers so answers are accurate, explainable, and consistent.
• Establish quality standards for data health, performance, and variability to ensure accurate and timely foundational data.
• Curate metadata and business context (descriptions, lineage, ownership, calculation logic) that make the data understandable to both humans and AI.

• Partner with data platform leadership to define the target architecture for scalable, AI-ready data solutions on Microsoft Fabric and Microsoft Azure, covering lakehouse and domain-oriented data product design, modeling, and a Fabric-based semantic model, and provide architectural direction to the engineering teams responsible for pipeline development and implementation.
• Organize data into business-aligned AI ready domains modernizing away from monolithic data warehouses and OLAP cubes toward governed, reusable data domains and data products with clear ownership, context model protocols, and contracts.
• Define reference architectures and patterns for ingestion, transformation, and serving that balance performance, cost, security, and maintainability for AI consumption.
• Guide the data platform roadmap in partnership with data platform leadership and the engineering teams responsible for implementation, performance tuning, and operational excellence.

• Connect the semantic model to consumption in Data Visualization platforms, ensuring dashboards and self-service analytics draw from governed, certified data sources.
• Integrate source data into the AI contextual enterprise model so revenue, pipeline, people, cost, and customer data are consistently defined and analytics-ready.
• Partner with BI developers and analysts to reduce duplicate logic and move shared definitions into the enterprise AI semantic model.

• Partner closely with the Data, BI & Analytics team to establish and lead the enterprise data governance operating model: data quality, lineage, access, certification, and stewardship across the stack, with clear policies, roles, and decision rights.
• Build and support in alignment with the…