Client Principal, Data Analytics and AI

Presidio

. Lead executive discovery, envisioning, assessments, and workshops .

Posted 9/29/2026full-timeRemote • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in data architecture, analytics, and cloud solutions, with a strong focus on translating business needs into actionable data products and measurable outcomes. Proven ability to lead cross-functional teams and deliver secure, outcome-aligned solutions across various cloud platforms.

Highest-signal resume keywords

Data Architecture LeadershipClient-Facing Technical Presales ExperienceETL/ELT Patterns ExpertiseData Governance and Quality PracticesCloud Platform Proficiency (AWS, Azure, Google Cloud)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data GovernanceETL/ELT PatternsCloud ArchitectureMachine Learning LifecycleDatabase ModernizationData Platform MigrationSemantic ModelingAnalytics SolutionsAI and GenAI SolutionsPresales Proposal Development

Soft Skills

Relationship BuildingExecutive Workshop FacilitationTechnical Delivery LeadershipRisk MitigationCommunication

Tools & Technologies

SnowflakeDatabricksMicrosoft FabricAI-Assisted Engineering ToolsData Cataloging Tools

Certifications & Qualifications

Relevant Data Platform CertificationsCloud Certifications

Industry Keywords

Data ProductsBusiness IntelligenceModern Data PlatformsResponsible AIRegulatory Compliance

Tech Stack

Tools & technologies

AWSAzureCloudETL

About the role

Key responsibilities & impact

Lead executive discovery, envisioning, assessments, and workshops
Translate ambiguous business problems into prioritized use cases, data products, and measurable outcomes
Build relationships across business, data, application, security, and cloud teams
Partner with account teams on opportunity qualification and account strategy
Define end-to-end architectures across ingestion, integration, storage, transformation, governance, analytics, ML, and GenAI
Create proposals and SOWs with scope, assumptions, staffing, estimates, risks, and dependencies
Ensure proposed approaches are viable, secure, supportable, outcome-aligned, and ready for delivery
Shape database, data platform, and cloud modernization roadmaps with hyperscaler and technology partners
Provide architectural leadership through discovery, proof-of-value, pilot, and early implementation
Mitigate technical risk and support presales-to-delivery handoff
Document outcomes, assumptions, decisions, estimates, and acceptance criteria
Recommend analytics, ML, AI, or GenAI solutions, including RAG, agents, grounding, evaluation, and guardrails
Apply data governance, cataloging, lineage, quality, and security-by-design practices

Requirements

What you’ll need

15+ years in data, analytics, software engineering, cloud architecture, consulting, or a related field
Significant client-facing technical presales experience as an architect, principal consultant, or senior solution leader
Customer implementation and technical delivery leadership experience
Proven ability to lead executive workshops, define solutions, write proposals and SOWs, and estimate delivery
ETL/ELT patterns across batch, streaming, and event-driven pipelines; lakehouse and modern warehouse concepts
Modeling for operational, analytical, semantic, and AI workloads; database modernization or platform migration experience
Enterprise BI, semantic modeling, and ML lifecycle/MLOps experience
RAG, agents, grounding, evaluation, guardrails, and responsible AI
Ability to advise across AWS, Azure, and Google Cloud and select services based on customer needs
Data governance, cataloging, lineage, quality, and security-by-design fluency
Working knowledge of scope, schedule, staffing, assumptions, dependencies, risk, margin, and delivery feasibility
Deep expertise in one modern data platform and practical experience in a second; ability to advise across Snowflake, Databricks, and Microsoft Fabric
Relevant data platform or cloud certifications and established partner relationships supporting joint go-to-market motions preferred
Experience adapting data and AI patterns to different industries, regulatory, and operating environments preferred
Software or full-stack engineering experience preferred
Experience building accelerators, assessment methods, reference architectures, or presales tools preferred
Experience using AI-assisted engineering and delivery tools with sound human review, security, IP, and governance practices preferred
Conference participation, published articles, or community contributions on modern data platforms and responsible AI preferred

Benefits

Comp & perks

Less than 25% travel
Equal Opportunity Employer
Reasonable accommodations for individuals with disabilities
Diverse and inclusive workplace commitment