below marketmost similar roles pay hereabove market
This role pays more than
60%
of similar roles. Most pay
$177,204–$253,437
— the blue band above.
At the midpoint, this role pays about
$225k
versus about
$215k
for comparable roles.
Based on 240 similar postings.
Employer
About SHI International
SHI International is a global IT solutions provider and Value-Added Reseller (VAR) that helps corporate, enterprise, and public sector customers manage, procure, and secure hardware, software, and cloud services.
SHI International currently has
55 open roles
on FindRole.
Listed pay typically runs
$120,000–$200,000
across 53 roles with salary data.
The Principal Architect - Data & AI works across data engineering, data visualization, data governance, and AI to orchestrate unified technical approaches for large, multi-disciplinary engagements. This role involves leading technical delivery, identifying risks, and driving practice maturation by establishing delivery standards, reusable accelerators, and engineering practices informed by DORA capabilities. The individual will build capabilities that outlast their tenure, including technical interview standards and skills inventories. Key responsibilities include coaching consultants, managing executive stakeholders, and applying AI tooling to improve consulting speed and quality. Required skills include expert-level depth in one data discipline and working proficiency in others, with hands-on experience in the Microsoft ecosystem, including Microsoft Fabric, Azure data services, Power BI, Microsoft Purview, Copilot Studio, and Microsoft Foundry.
What does a Architect earn?
Median $225000 from 45 postings across 26 companies.
Orchestrate a unified technical approach across data engineering, data visualization, data governance, and AI for large engagements.
Own the delivery structure, sequencing, staffing, and risk mitigation for multi-disciplinary projects.
Establish and maintain delivery standards, reusable accelerators, and engineering practices to ensure practice scalability.
Identify delivery risks early and intervene to maintain quality and coherence across workstreams.
Apply AI tooling and agentic patterns to improve the speed and consistency of consulting work.
Coach architects and consultants on delivery approach, consulting judgment, and technical decision-making.
Lead discovery, architecture reviews, and executive working sessions to drive technical decisions.
Support presales by providing scoping, effort modeling, and technical approach inputs for SOWs.
What we're looking for
Bachelor’s degree in a related technical field or equivalent professional experience.
Ten or more years of experience delivering enterprise data or AI solutions, including substantial experience in a consulting or professional services environment.
Expert-level depth in one of data engineering, data visualization, or data governance, with working proficiency in at least two of the others.
Demonstrated experience taking a practice capability from assessment through to an adopted standard.
Experience leading technical delivery across more than one discipline simultaneously on large or complex engagements.
Applied experience using AI to change how a delivery team works, with a clear account of what improved and what did not work.
Hands-on delivery experience within the Microsoft data and AI ecosystem, including Microsoft Fabric, Azure data services, Power BI, Microsoft Purview, Copilot Studio, or Microsoft Foundry.
Excellent facilitation, presentation, and stakeholder management skills, including with executive audiences.
Experience supporting presales through scoping, effort modeling, technical approach, and SOW input (preferred).
Familiarity with DORA capabilities and their application to data and analytics delivery (preferred).
Experience supporting regulated industry or public sector clients, including government, healthcare, financial services, or education (preferred).
Relevant Microsoft certifications, such as PL-300, DP-600, DP-700, DP-750, GH-300, GH-600, or AI-901 (preferred).
AI
Agentic Systems
Model Serving
Multi-model Orchestration
AWS
GCP
Azure
API
MCP
infrastructure-as-code
FinOps
Responsible AI
Model Evaluation
Guardrails
AI
LLM
Agentic Workflows
Vector Search
AI Orchestration
Distributed Systems
APIs
Cloud-Native
Data Platforms
AI Governance
Observability
Security
Privacy
Compliance