Principal Architect - Data & AI
New
J
JobgetherData & AI Consulting
USFull-TimePrincipal
Salary$200,000–$250,000, including base salary and bonus
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Job Details
- Experience
- 10+ years
- Required Skills
- Artificial IntelligenceMicrosoft Power BIData engineeringData visualization
Requirements
- Bachelor's degree in a related technical field or equivalent professional experience.
- 10+ years of experience delivering enterprise data or AI solutions, including substantial experience within consulting or professional services environments.
- Expert-level expertise in at least one of data engineering, data visualization, or data governance, combined with working proficiency across at least two additional disciplines.
- Demonstrated ability to take a practice capability from assessment through to an adopted and sustainable standard.
- Proven experience leading technical delivery across multiple disciplines simultaneously on large or complex engagements.
- Practical experience using AI to improve how delivery teams operate, with ability to demonstrate measurable outcomes.
- Hands-on experience within the Microsoft data and AI ecosystem (e.g., Microsoft Fabric, Azure data services, Power BI).
- Exceptional facilitation, presentation, communication, and stakeholder management skills.
- Ability to influence effectively without relying on direct reporting authority.
- Ability to travel periodically to client, partner, company, and industry event locations.
Responsibilities
- Lead the technical delivery approach for large, multidisciplinary engagements spanning data engineering, data visualization, data governance, and AI.
- Orchestrate technical leads across disciplines to establish a unified delivery plan, including sequencing, dependencies, decision points, and shared standards.
- Identify delivery risks early and intervene when engagements begin to drift in quality, technical coherence, or execution approach.
- Drive practice maturation initiatives from initial assessment through adoption, establishing documented standards, reusable accelerators, engineering practices, advisory frameworks, and clear ownership.
- Improve talent and engagement models through consistent technical interview standards, calibration frameworks, and skills visibility.
- Apply AI tooling and agentic patterns to consulting delivery, measuring their impact on speed, quality, consistency, and overall delivery economics.
- Coach architects and consultants across disciplines on consulting judgment, delivery strategy, and technical decision-making.
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