Senior Salesforce AI, Data Cloud & Analytics Architect

Fiserv•Coral Springs, FL

20h

About The Position

The Senior Salesforce AI, Data Cloud & Analytics Architect is a hands-on enterprise Subject Matter Expert (SME) for Salesforce Agentforce, Data Cloud (Data 360), and Tableau Next. The role partners with Solution Architects, Sales, Service, Marketing, Data Platform, Security, and Business teams to design and deliver AI-powered, data-driven capabilities across the Salesforce ecosystem. It combines technical and strategic contribution across platform architecture, agent design patterns, data model strategy, semantic layer standards, integrations, governance, and analytics enablement for enterprise customer intelligence and AI-driven processes. At the senior level, the role typically calls for 10+ years of experience in enterprise application architecture, CRM platforms, data platforms, analytics, AI-enabled solutions, or related fields, including 5+ years of Salesforce architecture experience supporting enterprise-scale initiatives. The architect serves as the primary SME for Agentforce, Data Cloud, and Tableau Next architecture, implementation patterns, governance, and adoption strategy; defines reusable standards and roadmaps; identifies and escalates risks; and influences enterprise strategy for AI adoption, customer intelligence, data activation, analytics modernization, and Salesforce platform consolidation.

Requirements

Typically 10+ years of experience in enterprise application architecture, CRM platforms, data platforms, analytics, AI-enabled solutions, or related technology domains.
5+ years of Salesforce architecture experience supporting enterprise-scale Sales, Service, Marketing, Data Cloud, analytics, or platform implementation initiatives.
Direct hands-on experience with Salesforce Agentforce, Einstein AI, Salesforce AI capabilities, or enterprise AI-enabled platform solutions.
Direct hands-on experience with Salesforce Data Cloud / Data 360, including data modeling, ingestion, identity resolution, segmentation, activation, or governance.
Experience with Tableau Next, Tableau, or equivalent enterprise analytics and semantic modeling platforms.
Strong Salesforce platform architecture experience across Sales Cloud, Service Cloud, Platform, integrations, security model, metadata, automation, and data architecture.
Experience designing customer 360 solutions, semantic data models, governed data products, and enterprise reporting or analytics frameworks.
Strong understanding of APIs, event-driven architecture, data integration patterns, middleware, cloud platforms, and enterprise data platforms such as Snowflake.
Experience defining architecture standards, solution designs, technical roadmaps, governance models, and implementation patterns for enterprise platforms.
Strong knowledge of data governance, privacy, compliance, access controls, auditability, and security expectations in regulated enterprise environments.
Excellent executive communication, stakeholder management, technical translation, documentation, and cross-functional leadership skills.

Nice To Haves

Salesforce Certified Technical Architect (CTA) or Salesforce Architect-level certifications.
Salesforce Data Cloud Consultant Certification.
Salesforce AI Specialist, AI Associate, or related Salesforce AI certifications.
Tableau certifications or hands-on experience delivering enterprise Tableau analytics solutions.
Experience with Snowflake, Snowflake Cortex, semantic layers, AI/ML platforms, or enterprise data lakehouse / medallion architecture patterns.
Experience integrating Salesforce with Snowflake, AWS, Azure, Google Cloud, middleware, API gateways, or enterprise data platforms.
Experience leading enterprise AI governance, Responsible AI adoption, platform modernization, or customer intelligence initiatives.
Experience within financial services, payments, fintech, or other highly regulated industries.
Experience working in Agile delivery models with product owners, architects, engineering teams, QA, security, and operations teams.
Fiserv products experience.

Responsibilities

Serve as the enterprise SME for Salesforce Agentforce capabilities, AI agent design, and AI-enabled business processes.
Design and support Agentforce agents, agent actions, orchestration patterns, prompts, grounding strategies, and enterprise use cases.
Partner with business stakeholders to identify, assess, prioritize, and implement AI automation opportunities across Sales, Service, Marketing, and Operations.
Define Responsible AI practices, security guardrails, approval patterns, escalation rules, testing approaches, and operational controls for production AI agents.
Translate business objectives into practical, secure, scalable, supportable Agentforce solution designs aligned with enterprise architecture standards.
Design and govern Salesforce Data Cloud architecture for customer 360, identity resolution, segmentation, activation, analytics, and AI use cases.
Define enterprise customer data models, canonical entities, data mapping standards, harmonization approaches, and stewardship practices.
Architect ingestion and integration of data from Salesforce, Snowflake, marketing platforms, service systems, ERP platforms, APIs, and other enterprise sources.
Support batch, near real-time, and event-driven data patterns for Agentforce, Tableau Next, personalization, analytics, and operational workflows.
Establish data quality, lineage, certification, access control, privacy, and governance expectations for Salesforce Data Cloud data products.
Serve as a technical SME for Tableau Next and Salesforce analytics capabilities supporting governed reporting, insights, and AI-assisted analytics.
Design semantic models, reusable business metrics, KPI definitions, dimensions, measures, and analytic frameworks.
Partner with business leaders and analysts to deliver executive dashboards, operational reporting, self-service analytics, and natural language insight experiences.
Define best practices for data visualization, semantic governance, dashboard performance, certified assets, user enablement, and analytics lifecycle management.
Ensure Tableau Next solutions align with enterprise data governance standards and integrate appropriately with Data Cloud, Snowflake, and other trusted data sources.
Define integration patterns connecting Salesforce, Data Cloud, Snowflake, APIs, middleware, cloud platforms, and enterprise systems.
Collaborate with engineering teams to design secure, scalable, maintainable, and observable platform solutions.
Evaluate emerging Salesforce AI, Agentforce, Data Cloud, Tableau Next, and platform capabilities and recommend practical adoption strategies.
Create reference architectures, solution designs, standards, decision records, technical roadmaps, and implementation guidance for delivery teams.
Support CRM consolidation, customer data unification, analytics rationalization, and AI-enabled workflow automation modernization efforts.
Provide technical leadership, mentoring, and guidance to architects, developers, administrators, analysts, and implementation partners.
Lead design workshops, architecture reviews, proof-of-concepts, demos, technical assessments, and executive-level solution walkthroughs.
Establish governance frameworks for platform scalability, compliance, security, data access, model quality, AI behavior, and operational readiness.
Partner with Salesforce account teams, implementation partners, enterprise architecture, information security, and business stakeholders to drive successful outcomes.
Champion adoption of Salesforce AI, data, and analytics capabilities while ensuring solutions are practical, secure, governed, and aligned with enterprise priorities.
Identify and escalate platform, security, data quality, compliance, integration, scalability, and operational risks to Solution Architects, platform leadership, and enterprise architecture teams.
Define reusable architecture standards, reference designs, platform guardrails, and technical roadmaps for Salesforce AI, data, and analytics capabilities.
Influence enterprise strategy related to AI adoption, customer intelligence, data activation, analytics modernization, and Salesforce platform consolidation.