Client Principal, Data Analytics and AI

Presidio, Where Teamwork and Innovation Shape the FutureAt 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 Role

The Client Principal, Digital Data, Analytics and AI lead executive discovery, opportunity strategy, and solution shaping for enterprise data and AI engagements. The role partners with account teams, architects, delivery leaders, and technology partners to turn complex business challenges into compelling, commercially viable solutions and successful delivery mobilization. This role reports to the Managing Client Principal and involves less than 25% travel.

Who You Are

• A Data-First Mind: You start with the client’s business and data challenge, ask strong questions, and bring a clear point of view even when the problem is still emerging.
• Executive Presence: You build trust with senior leaders, create consensus, and make complex data and AI concepts easy to understand.
• Storyteller: You connect architecture and technology choices to outcomes clients can see and measure.
• Resilient and Determined: You navigate ambiguity, stay focused, and move difficult opportunities forward.
• Builder Mindset: You want to help build a differentiated Data & AI consultancy grounded in client partnership, design thinking, and measurable value.

Responsibilities Include

• Client Advisory & Opportunity Leadership: Lead executive discovery, envisioning, assessments, and workshops; translate ambiguous problems into prioritized use cases, data products, and measurable outcomes.
• Trusted Relationships: Build relationships across business, data, application, security, and cloud teams; partner with account teams on opportunity qualification and account strategy.
• Solution Architecture: Define end-to-end architectures across ingestion, integration, storage, transformation, governance, analytics, ML, and GenAI, with depth in modern data platforms.
• Proposal, SOW & Commercialization: Create proposals and SOWs with clear scope, assumptions, staffing, estimates, risks, and dependencies.
• Solution Quality: Ensure proposed approaches are viable, secure, supportable, outcome-aligned, and ready for delivery.
• Modernization Roadmaps: Shape database, data platform, and cloud modernization roadmaps with hyperscaler and technology partners while maintaining a platform-neutral posture.
• Delivery Mobilization: Provide architectural leadership through discovery, proof-of-value, pilot, and early implementation; mitigate technical risk.
• Presales-to-Delivery Handoff: Document outcomes, assumptions, decisions, estimates, and acceptance criteria for a clean transition to delivery.
• AI and GenAI Advisory: Recommend analytics, ML, AI, or GenAI when appropriate, including RAG, agents, grounding, evaluation, and guardrails.
• Governance & Security: Data governance, cataloging, lineage, quality, and security-by-design fluency.

Modern Data Platform Expertise

Deep expertise in one modern data platform and practical experience in a second is required. The role should be able to advise across Snowflake, Databricks, and Microsoft Fabric.

Required Skills and Professional Experience

• Experience: 15+ years in data, analytics, software engineering, cloud architecture, consulting, or a related field.
• Presales Background: Significant client-facing technical presales experience as an architect, principal consultant, or senior solution leader.
• Delivery Leadership: Customer implementation and technical delivery leadership experience.
• Workshop & Proposal Skills: Proven ability to lead executive workshops, define solutions, write proposals and SOWs, and estimate delivery.
• Data Engineering: ETL/ELT patterns across batch, streaming, and event-driven pipelines; lakehouse and modern warehouse concepts.
• Data Modeling & Modernization: Modeling for operational, analytical, semantic, and AI workloads; database modernization or platform migration experience.
• Analytics & ML: Enterprise BI, semantic modeling, and ML lifecycle/MLOps experience.
• GenAI Fluency: RAG, agents, grounding, evaluation, guardrails, and responsible AI.
• Cloud Breadth: Ability to advise across AWS, Azure, and Google Cloud …