Technical Architect Director - PubSec - Mulesoft

Salesforce•McLean, VA

2d•$178,900 - $344,700•Remote

About The Position

The Director, Data Foundation Delivery is a senior leader who owns the strategy, architecture, and successful delivery of enterprise Data Foundation engagements for Salesforce Professional Services customers. Drawing on 15+ years of deep data experience, you set the technical vision, advise customer executives at the CxO level, and lead the delivery of a governed, AI-ready data foundation across a progressive, customer-calibrated maturity journey. You are the definitive authority on bringing the Data Foundation Delivery to life including core data capabilities, associated frameworks, and ability to operate across one or more of the platform stack (Salesforce Data 360, Informatica IDMC, MuleSoft). As a Salesforce leader, you help customers bring the Salesforce ecosystem into the broader landscape of technology investments they have already made — directing both 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. Above all, you champion AI-based professional services delivery: you set the standard for how engagements use AI tools like (Claude Code, Gemini, Lucid AI, NotebookLM) to compress delivery effort while raising quality and consistency, and you author the reusable IP — prompt templates, skills, and agents — that scales delivery. You are an industry thought leader who shapes the practice's point of view on the agentic future of the SaaS industry, translating where enterprise data, AI agents, and the SaaS ecosystem are heading into how we advise and deliver for customers today. This is a customer-billable delivery role — a senior individual contributor accountable for engagement outcomes and hands-on technical leadership, not an internal people-management position.

Requirements

15+ years of deep, hands-on data experience across data architecture, engineering, MDM, integration, and governance
Demonstrated leadership of enterprise-scale data platform and AI-readiness programs
Deep expertise across one or more of Salesforce Data 360, Informatica IDMC, MuleSoft
Authority-level data modeling and semantic/metadata modeling
Strong command of data governance, quality, security, and privacy (e.g., GDPR/CCPA/HIPAA)
Proven CxO-level advisory and the ability to lead multi-workstream delivery
Track record integrating a vendor platform into complex, heterogeneous enterprise landscapes — balancing platform-agnostic (open-standards, multi-vendor) and platform-centric (Salesforce-native) approaches
Deep fluency leading AI-augmented delivery — using AI tools as a core part of the workflow and building reusable prompt/skill/agent assets
Recognized industry thought leadership on enterprise data, AI, and the agentic future of SaaS (POVs, speaking, published perspectives)
8 - 10 years experience supporting customers using Mulesoft(required).
Experience with deep MuleSoft Anypoint Platform expertise
Strong understanding of how MuleSoft solves business problems:
API-led connectivity: Three-layer architecture enabling reusability and agility
Integration patterns: Real-time sync, batch processing, event-driven architectures
API Management: Governance, security policies, rate limiting
Deployment options: CloudHub vs Runtime Fabric - when to use each
Knowledge of MuleSoft + Salesforce integration (Salesforce Connector, Composer, Data Cloud)
Understanding of when to engage technical resources for complex integrations
Understanding of integration patterns with enterprise systems (SAP, Oracle, Workday, ServiceNow)
Familiarity with MuleSoft RPA capabilities
Multiple MuleSoft certifications (Developer + Integration Architect Associate)
Candidates must reside in the DMV area. Although this is a remote-first position, local residency is required for occasional on-site client visits.
Bachelor’s degree (or its foreign degree equivalent) in Computer Science, Engineering (any field), or a related quantitative discipline. Equivalent demonstrable work experience in lieu of a degree will be considered
Ability to convey and convince customers of best practices at various levels within a large organization
Application design and development background
Have CTA certification or are in the process of getting the CTA
Experience managing large full life-cycle Salesforce Implementations
Executive Presence - being able to influence outcomes
Strong understanding of SDLC methodologies (Agile, SCRUM)

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
Salesforce Data Cloud Consultant
Salesforce Certified Data Architect
Salesforce Agentforce Specialist
Salesforce Certified Integration Architect
TOGAF
Informatica IDMC / MDM certification
MuleSoft Certified Integration Architect
DAMA CDMP or CDMC (data management / cloud data management)
Track record delivering agentic AI / RAG on a governed data foundation
Deep industry expertise in Financial Services, Healthcare, or Manufacturing
History of building delivery IP, accelerators, and prompt/skill/agent libraries
Extensive Professional Services / customer-facing leadership at enterprise scale

Responsibilities

Serve as trusted advisor to customer CxOs; shape data strategy and the business case
Own executive discovery, maturity assessment, and the phased, customer-calibrated roadmap
Frame guidance as adaptable options, meeting customers at their entry point (customer-360, regulatory governance, analytics modernization, unstructured/RAG)
Represent the practice in the most complex, high-stakes engagements
Set target-state architecture across Data 360 / Informatica IDMC / MuleSoft
Balance platform-agnostic and platform-centric execution — position Salesforce as the center of gravity while integrating cleanly with the customer's existing multi-vendor technology investments (data platforms, warehouses, lakes, and tools)
Approve architecture decisions; validate through scoped POCs before production build
Ensure value is delivered every phase (no big-bang), with governance-first discipline
Guarantee dual-consumption design: 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
Ensure security, privacy, and governance controls are embedded from the start
Set the standard for AI-augmented professional services delivery — embed AI tools (Claude Code, Gemini, Lucid AI, NotebookLM) across the full engagement lifecycle to compress effort and raise quality
Define the practice's approach to capability-driven (not tool-centric) reusable assets — prompt templates, skills, and agents that any consultant can run to deliver a capability
Establish measurable AI-acceleration targets and quality guardrails; institutionalize what works into the playbook
Ensure human-at-the-helm governance so AI-accelerated delivery stays trusted, auditable, and grounded
Own the practice's point of view on the agentic future of the SaaS industry — where enterprise data, AI agents, and the SaaS ecosystem are heading, and what it means for customers
Translate that vision into how we advise and deliver: reference architectures, POVs, and forward-looking roadmaps for AI-ready, agent-native data foundations
Represent the practice externally and internally — publish POVs, brief executives, and shape the market conversation
Bring experience-based thought leadership into engagements, positioning customers ahead of the agentic shift
Author and evolve the Data Foundation Delivery Playbook, accelerators, and reference IP
Provide hands-on technical leadership to the engagement delivery team; guide Senior Advisors, Architects, and Consultants on the account
Establish stewardship, RACI, and sustainable customer operating models
Ensure executive-ready summaries accompany deep technical detail on every engagement