Solutions Architect - Data Visualization

SHI International Corp.US - TX - Home Office, TX
$160,000 - $215,000Hybrid

About The Position

The Solutions Architect, Data Visualization is a lead technical and strategic advisor for enterprise business intelligence initiatives in client engagements. This role works directly with stakeholders, business leaders, analyst communities, and technical delivery teams to design and implement analytics solutions that people trust, understand, and use to make decisions. The focus of this client-facing delivery role is enterprise data visualization, including semantic model architecture, reporting standards, human-centered design, accessibility, governed self-service enablement, performance optimization, and Power BI implementation at scale. The Solutions Architect defines the analytics approach, designs reporting and semantic architectures, leads customer engagements, and provides oversight throughout delivery of the visualization workstream. This role spans both technical leadership and hands-on-keyboard development. This role also advises organizations on analytics readiness for modern data and AI platforms, including Microsoft Fabric and Power BI.

Requirements

  • Bachelor's degree in Analytics, Information Design, Information Systems, Computer Science, a related technical field, or equivalent professional experience.
  • Five or more years delivering enterprise analytics, business intelligence, or data visualization solutions, with substantial focus on Power BI.
  • Hands-on implementation experience with Power BI at enterprise scale, including dimensional modeling, semantic model design, Power Query, DAX, Tabular Editor, and performance tuning.
  • Demonstrated experience designing an enterprise reporting architecture adopted across an organization, including security, workspace, and endorsement models.
  • Demonstrated experience leading customer-facing consulting engagements, executive workshops, design reviews, and strategic advisory initiatives.
  • Demonstrated experience with Microsoft Fabric, Power BI, and Direct Lake semantic models.
  • Demonstrated application of human-centered design and information design principles on enterprise reporting solutions, with working knowledge of accessibility standards.
  • Experience with data engineering and data governance architectures and how they relate to data visualization.
  • Excellent communication, facilitation, presentation, and stakeholder management skills.
  • Ability to travel to SHI, partner, and customer locations as needed.
  • Ability to work independently while collaborating effectively with sales, delivery, engineering, and leadership stakeholders.
  • Commitment to continuous learning across data visualization, analytics, and AI platforms.
  • Strong ethical standards with disciplined adherence to data privacy, governance, compliance, and security policies.

Nice To Haves

  • Experience creating custom Power BI visuals using Deneb, Vega-Lite, or comparable visualization frameworks.
  • Experience with Azure Databricks and Lakehouse architectures on Azure.
  • Experience supporting Microsoft 365 Copilot enablement for analytics.
  • Exposure to data governance practices, including Microsoft Purview, cataloging, and lineage as they relate to analytics assets.
  • Experience with Azure DevOps, GitHub, Infrastructure as Code (IaC), and CI/CD practices supporting Power BI deployments.
  • Experience establishing analytics centers of excellence, champion programs, or author enablement communities.
  • Experience working within regulated industries including healthcare, financial services, insurance, manufacturing, or public sector organizations.

Responsibilities

  • Act as a lead subject matter expert for enterprise data visualization, reporting architecture, human-centered design, and analytics adoption.
  • Lead discovery workshops, analytics maturity assessments, roadmap engagements, and executive strategy sessions that establish what the organization needs to measure and why.
  • Design enterprise reporting architectures including semantic model strategy, workspace and app structure, certification and endorsement models, reusability standards, and the boundaries of self-service enablement.
  • Architect and oversee implementation of Power BI solutions including semantic models, Power Query transformations, DAX calculation logic, composite and Direct Lake models, and performance optimization for large models and high user concurrency.
  • Design row-level and object-level security models and workspace access architectures that serve internal and external audiences without fragmenting the reporting estate.
  • Guide integration between Power BI and the broader data estate across Microsoft Fabric, OneLake, Azure Data Services, and upstream data engineering workstreams.
  • Serve as a trusted advisor to executive stakeholders, business leaders, analyst communities, and technical teams.
  • Translate business objectives and decision-making needs into scalable analytics solutions, including advising when a report is not the right answer to the question being asked.
  • Lead design reviews and enablement activities that build client capability to sustain and extend the solution after the engagement ends.
  • Establish design and accessibility standards for enterprise reporting, including visual design systems, report templates, and interaction patterns that scale across multiple authors and align with WCAG 2 and Section 508 standards within platform capabilities.
  • Define delivery quality practices for analytics workstreams, including semantic model review, performance testing, documentation, version control, and deployment pipelines.
  • Contribute visualization accelerators and reusable delivery assets from engagement experience.
  • Apply the practice's delivery standards and AI-accelerated delivery patterns on engagements and identify where adjustments are needed based on real-world client conditions.
  • Advise organizations on analytics readiness for Microsoft 365 Copilot and AI-assisted reporting experiences.
  • Assess semantic model quality, naming conventions, documentation, and metadata maturity required for AI-assisted analytics to return trustworthy answers.

Benefits

  • medical
  • vision
  • dental
  • 401K
  • flexible spending
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