Senior Technical Architect / Technical Architect Director - Data Foundation Delivery

Salesforce•Indiana - Remote, IN

1d•$172,500 - $313,700

About The Position

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.

Requirements

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

Nice To Haves

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
Certifications are preferred, not required — a proven delivery and thought-leadership track record carries the most weight.
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)
Informatica IDMC / MDM certification
Salesforce Agentforce Specialist (Sr. Architect level)
MuleSoft Certified Integration Architect (Director level)
DAMA CDMP or CDMC
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

Responsibilities

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
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
Provide architectural governance and quality assurance across concurrent engagements
Own delivery risk: exec buy-in, business engagement, scope, and dependency management
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
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
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)