Principal Architect - Data & AI

About Us

Since 1989, SHI International Corp. has helped organizations change the world through technology. We’ve grown every year since, and today we’re proud to be a $16 billion global provider of IT solutions and services.

Over 17,000 organizations worldwide rely on SHI’s concierge approach to help them solve what’s next. But the heartbeat of SHI is our employees – all 7,000 of them. If you join our team, you’ll enjoy:

Our commitment to diversity, as the largest minority- and woman-owned enterprise in the U.S.

Continuous professional growth and leadership opportunities.

Health, wellness, and financial benefits to offer peace of mind to you and your family.

World-class facilities and the technology you need to thrive – in our offices or yours.

Job Summary

The Principal Architect works across data engineering, data visualization, data governance, and AI rather than within a single technical area. On large, multi-disciplinary engagements, this role orchestrates a unified technical approach across technical area leads, each of whom owns depth within their own discipline. Alongside that delivery leadership, this role carries the practice maturation agenda: the delivery standards, accelerators, engineering practices, evaluation rubrics, and advisory frameworks that make delivery consistent and repeatable as the practice scales. The Principal Architect may be billable on engagements where specific technical depth or cross-discipline technical leadership is required.

Role Description

Cross-Practice Delivery Leadership

Lead the technical delivery approach on large, multi-disciplinary engagements spanning data engineering, data visualization, data governance, and AI.

Orchestrate a unified solution approach across capability leads, integrating each discipline’s technical direction into one coherent delivery plan with clear sequencing, dependencies, and shared standards.

Own delivery approach rather than solution design within any single discipline: how the work is structured, sequenced, staffed, and de-risked, and where the technical decision points sit.

Identify delivery risk early and intervene on engagements drifting on approach, quality, or coherence across workstreams.

Practice Maturation

Priorities are set with the Practice Manager, each carried from assessment through to an adopted standard.

Delivery Excellence: baseline delivery standards, reusable accelerators and templates, engineering practices informed by DORA capabilities, and adaptive delivery approaches that balance program predictability with the experimentation required by data and AI projects .

Talent and Engagement Model: technical interview standards and calibration, a consistent hiring bar, skills inventory and workforce visibility, and engagement health practices that protect consultant focus.

Scoping and Advisory Excellence: structured recommendation frameworks, strategic opportunity framing that translates vague asks into clarified business problems, and clearer engagement pathways between delivery, presales, and the PMO.

Data and AI Fluency: capability assessment, targeted learning pathways mapped to assessment outcomes and to the pace of Microsoft platform change, and improved use of internal data for practice decision-making.

Build capabilities so they outlast the person driving them, with documented standards, named owners, and adoption evidence .

AI-Accelerated Delivery

Apply AI tooling and agentic patterns to how the practice delivers value , improving the speed, consistency, and quality of consulting work across all engagements .

Evaluate where AI meaningfully changes delivery economics and where it introduces review overhead without net gain and build the evidence to distinguish the two.

Fold proven patterns into delivery standards and accelerators so that gains are structural to the practice rather than dependent on individual habit .

Practice Leadership and Capability Growth

Coach architects and consultants across disciplines on delivery approach, consulting judgment, and technical decision-making. This is a player-coach role without direct reporting relationships.

Influence the priorities of technical leads where cross-practice coherence, engagement risk, or the practice maturation agenda requires it.

Behaviors and Competencies

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This role sits at the top of the technical career architecture and is expected to demonstrate expert-level capability across the following.

Subject Matter Expertise: Recognized depth in one discipline and sufficient working command of others to lead delivery, evaluate technical decisions, and identify risk outside their primary area.

Facilitation: Leads discovery, architecture review, and executive working sessions to a decision, including where stakeholders disagree or the problem is poorly defined at the outset.

Communication: Explains complex technical trade-offs to executive, business, and technical audiences, and enables effective communication between groups that do not naturally align.

Relationship Management: Builds durable trust with client executives, internal leadership, partners, and delivery teams, and sustains it through difficult engagements.

Collaboration: Works in the open across technical disciplines , presales, PMO, and partner organizations, treating shared outcomes as the measure of success. Collaborates closely with Principal Architects from other delivery teams to enable consistent delivery approach and continuous improvement within SHI Services.

Problem Solving: Anticipates systemic problems, addresses root causes rather than symptoms, and proposes solutions that hold up as the practice scales.

Skill Level Requirements

We are looking for candidates who demonstrate strength across these areas. Deep expertise in every technology listed is not expected. Candidates should not self-select out if they do not meet all of them.

Bachelor’s degree in a related technical field, or equivalent professional experience.

Ten or more years 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 sufficient to lead delivery and evaluate technical decisions across them.

Demonstrated experience taking a practice capability from assessment through to an adopted standard. Examples include delivery standards, engineering or DevOps practices, accelerator libraries, interview and calibration frameworks, or competency models. Candidates should be prepared to describe what was adopted, and whether it survived after they stopped driving it.

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, how it was measured, and what did not work.

Hands-on delivery experience within the Microsoft data and AI ecosystem, which may include Microsoft Fabric, Azure data services, Power BI, Microsoft Purview, Copilot Studio, or Microsoft Foundry, aligned to the candidate’s area of depth.

Excellent facilitation, presentation, and stakeholder management skills, including with executive audiences.

Ability to work effectively through influence rather than reporting authority.

Preferred Skills and Experience

Experience supporting presales through scoping, effort modeling, technical approach, and SOW input.

Familiarity with DORA capabilities and their application to data and analytics delivery.

Experience supporting regulated industry or public sector clients, including government, healthcare, financial services, or education.

Relevant Microsoft certifications, which may include PL- 300 , DP-600, DP-700 , DP-750, GH-300, GH-600, or AI-901.

Other Requirements

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