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Job Category
Customer Success
Job Details
This role leads the advisory, architecture, and delivery of enterprise Data Foundation engagements for Salesforce Professional Services customers. Drawing on deep data experience (10+ years for the Senior Technical Architect level; 15+ years for the Director level), you run discovery, set the technical vision, design/approve the target architecture, and drive delivery across a progressive, customer-calibrated maturity journey - advising customer stakeholders (up to CxO level at the Director tier) along the way.
You bring the Data Foundation Delivery to life, including core data capabilities, associated frameworks, and the ability to operate across one or more of the platform stack (Salesforce Data 360, Informatica IDMC, MuleSoft). As a Salesforce practitioner/leader, you help customers bring the Salesforce ecosystem into the broader landscape of technology investments they've already made - balancing platform-agnostic execution (interoperable, open-standards, multi-vendor) and platform-centric execution (Salesforce-native), so the data foundation fits the customer's reality rather than forcing a single stack. Every foundation is built with governance, quality, security, and privacy embedded from day one, and serves both traditional analytics for people and agentic AI for machines.
You are a hands-on practitioner of AI-augmented professional services delivery and an emerging-to-established thought leader on the agentic future of the SaaS industry - applying a forward-looking perspective on enterprise data, AI agents, and the SaaS ecosystem to how you advise and deliver, and contributing that experience back to the practice's point of view. This is a customer-billable delivery role - a hands-on/senior individual contributor accountable for engagement outcomes and technical leadership, not an internal people-management position.
What You Will Do (Key Responsibilities)
Advisory & Strategy
- Lead discovery: stakeholder interviews, current-state assessment, use-case and KPI definition; at senior levels, serve as trusted advisor to customer CxOs and shape the business case
- Assess data maturity and build a phased, customer-calibrated roadmap
- Align customer stakeholders and sponsors; contribute to/own the business case and expected outcomes
- Frame guidance as adaptable options, meeting customers at their entry point (customer-360, regulatory governance, analytics modernization, unstructured/RAG)
- Represent the practice in complex, high-stakes engagements
Architecture & Delivery
- Design/set/approve target-state architecture across one or more of the platform stack (Salesforce Data 360 / Informatica IDMC / MuleSoft)
- Deliver both platform-agnostic and platform-centric execution - integrate Salesforce cleanly with (or position it as the center of gravity within) the customer's existing multi-vendor technology investments (data platforms, warehouses, lakes, and tools)
- Validate architecture decisions through scoped POCs before production build
- Deliver working software/value every phase - no big-bang, governance-first discipline
- Embed governance, quality, security, and privacy from the start
- Build for dual consumption: analytics for people and agentic AI for machines
Delivery Oversight & Risk (Director-level emphasis)
- Provide architectural governance and quality assurance across concurrent engagements
- Own delivery risk: exec buy-in, business engagement, scope, and dependency management
AI-Augmented Delivery
- Apply/set the standard for AI-augmented professional services delivery - use AI tools (Claude Code, Gemini, Lucid AI, NotebookLM) across the engagement lifecycle to compress effort and raise quality
- Build (or define the approach for) reusable, capability-driven (not tool-centric) assets: prompt templates, skills, and agents that deliver a capability regardless of underlying tool
- Work with human-at-the-helm rigor so AI-accelerated output stays trusted, auditable, and grounded; at senior levels, set measurable AI-acceleration targets and quality guardrails
- Contribute proven patterns and assets back to the practice's playbook, accelerators, and reference IP
Industry Thought Leadership (Agentic SaaS Future)
- Bring (or own) a forward-looking perspective on the agentic future of the SaaS industry into engagements - helping customers build AI-ready, agent-native data foundations
- Contribute to (or shape) the practice's point of view - POVs, reference patterns, and enablement on where enterprise data and AI agents are heading
- Grow as, or represent the practice as, an internal and customer-facing voice on agentic delivery
Governance & Enablement
- Establish stewardship, RACI, and sustainable operating models with the customer
- Produce clear, concise, executive-ready summaries alongside deep technical detail
- Provide hands-on technical guidance/leadership to Consultants, Architects, and (at Director level) Senior Advisors on the engagement; hand off with runbooks and a sustainable operating model
- Author and evolve the Data Foundation Delivery Playbook, accelerators, and reference IP (Director level)
What You Bring (Preferred Experience)
- Unified Identity & Harmonization - identity resolution, match/merge, golden records
- Master Data Management - domains, survivorship, hierarchies, 360 views
- Unstructured Data Management - document ingestion, chunking, embeddings, RAG grounding
- Data Architecture & Semantic Modeling - conceptual/logical/physical models, semantic layer, glossary
- Data Integration, Orchestration & Activation - API-led connectivity, CDC, real-time events, activation
- Data Trust, Security & Privacy - classification, access control, masking, Einstein Trust Layer
- Data Governance & Stewardship - catalog, lineage, data quality, stewardship & policy
- Industry Data Models & Accelerators - FSC, Health Cloud, Manufacturing Cloud blueprints
- Data Platform & Infrastructure - lakehouse, compute, catalog, cloud foundation
- Analytics, BI & Data Observability - dashboards, self-service BI, freshness/quality monitoring
Required Qualifications
- 10+ years (Senior Technical Architect) / 15+ years (Director) of hands-on data experience across data & analytics consulting, engineering, architecture, MDM, integration, and governance
- Demonstrated delivery/leadership of enterprise data platform, MDM, integration, governance, or AI-readiness programs
- Hands-on/deep expertise with one or more of Salesforce Data 360, Informatica IDMC, MuleSoft
- Strong-to-authority-level data modeling (conceptual/logical/physical) and semantic/metadata modeling
- Working-to-strong command of data governance, quality, security, and privacy (e.g., GDPR/CCPA/HIPAA)
- Executive-grade communication, up to proven CxO-level advisory at senior levels; ability to guide delivery teams and lead multi-workstream delivery
- Experience integrating a vendor platform into heterogeneous/complex enterprise landscapes - balancing platform-agnostic and platform-centric approaches
- Hands-on-to-deep fluency with AI-augmented delivery - using AI tools as a core part of the workflow and building reusable prompt/skill/agent assets
- A forward-looking, and at senior levels recognized/published, perspective on enterprise data, AI, and the agentic future of SaaS
Certifications
Certifications are preferred, not required - a proven delivery and thought-leadership track record carries the most weight.
Preferred Certifications
- Salesforce Data Cloud Consultant
- Salesforce Certified Data Architect
- Salesforce Certified Integration Architect
- Salesforce Agentforce Specialist (Director)
- MuleSoft Certified Integration Architect (Sr. Architect level)
- TOGAF (Director)
Additional Pluses
- Informatica IDMC / MDM certification
- Salesforce Agentforce Specialist (Sr. Architect level)
- MuleSoft Certified Integration Architect (Director level)
- DAMA CDMP or CDMC
Preferred / Differentiating Strengths
- Experience/track record delivering agentic AI / RAG on a governed data foundation
- Industry depth/expertise in Financial Services, Healthcare, or Manufacturing (industry data models)
- Track record/history building reusable accelerators and prompt/skill/agent libraries
- Prior Professional Services / customer-facing advisory or leadership experience at enterprise scale
How Success Is Measured (First 12 Months)
- Certification Attainment: complete required certifications to be compliant and ready for customer engagements
- Discovery-to-roadmap / Customer impact: consistently produce customer-calibrated maturity assessments and roadmaps that secure signed charters; ramp quickly to be billable on one or more engagements
- Delivery / Architecture standard: ship working, governed capability increments each phase, with consistent, governed, dual-purpose foundations across the portfolio
- Advisory impact / Business outcomes: measurable stakeholder alignment and adoption; clear business (not just technical) outcomes realized
- AI-augmented delivery: apply AI tooling to reduce delivery effort while improving consistency; contribute reusable prompt/skill/agent assets to the practice, adopted team-wide at senior levels
- Thought leadership: bring a credible agentic-SaaS-future perspective into engagements; at Director level, own a defined, published practice POV shaping customer engagements and market positioning
- Governance / Enablement: leave every engagement with a sustainable stewardship and operating model; delivery teams ramped and productive through technical leadership
