Data Solutions Architect

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. The posting includes description of role, responsibilities, qualifications, etc. No explicit Benefits, Pay, Schedule mentioned. So we should not include those sections. Also we need to use

for section headings. Use

• for any list of duties/requirements/benefits, and

  for prose. We need to preserve all substantive information, not invent or summarize away detail. Remove boilerplate etc. We need to decide sections: About the role (maybe intro paragraph), Responsibilities (list of duties), Requirements (maybe required qualifications), Qualifications (maybe preferred qualifications?), Skills (maybe list of skills). The posting includes "What You'll Do" (responsibilities), "What You'll Bring" (required qualifications), "Preferred Qualifications", "Additional Differentiators". Also "Why Quisitive?" maybe about company but could be considered About the role? Actually "About the role" could be the introductory paragraph: "Build Modern Data Platforms That Drive Business Outcomes At Quisitive, we help organizations turn data into a strategic asset. As a Data Solutions Architect, you will lead the design and delivery of modern analytics solutions..." That's about role. We need to avoid repeating job title as heading. So we will not put heading for job title. We need to include sections only when posting has real specific content. So we can have:

  About the role

  with paragraph(s) from intro.

  Responsibilities

  with list from "What You'll Do" bullet points (though they are paragraphs with bold headings). We'll extract each bullet as list items.

  Requirements

  with required qualifications list.

  Qualifications

  maybe for preferred qualifications? Or we could combine required and preferred under Requirements and Qualifications? The instruction says use sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content accordingly. We have required qualifications (mandatory) -> Requirements. Preferred qualifications -> Qualifications. Skills: maybe we can extract skills from required/preferred like "Advanced knowledge of data modeling..." etc. But those are already in qualifications. Could create Skills section listing technical skills: Microsoft Fabric, Azure Data Services, Databricks, Power BI, Microsoft Purview, PySpark, SQL, etc. But we must not invent or summarize away detail; we can list them as they appear. The posting includes many specific technologies; we can put them in Skills. We must not create Benefits, Pay, Schedule sections because not mentioned. We must not include boilerplate like EEO etc. We need to output only HTML fragment. Let's extract content. Intro paragraph: "Build Modern Data Platforms That Drive Business Outcomes At Quisitive, we help organizations turn data into a strategic asset. As a Data Solutions Architect, you will lead the design and delivery of modern analytics solutions using Microsoft Fabric, Azure Data Services, Power BI, Microsoft Purview, and Databricks. You will partner with clients and delivery teams to architect scalable, secure data platforms that improve reporting, analytics, automation, and AI readiness. This is a client-facing leadership role where you will guide organizations through discovery, solution design, architecture, estimation, and delivery while serving as the technical lead for data and analytics engagements." That's about role. Responsibilities: Under "What You'll Do" there are headings: Lead Architecture & Solution Design, Partner with Clients, Build Trusted Data Foundations, Enable AI & Innovation. Under each there are bullet-like sentences. We'll convert each sentence into
• . Let's list them: Lead Architecture & Solution Design: - Own the technical architecture and solution direction for client engagements. - Design Microsoft Fabric, Azure, Databricks, and hybrid analytics platforms aligned with business goals, scalability, governance, and cost requirements. - Architect data integration, Lakehouse, data warehouse, semantic modeling, Power BI, and self-service analytics solutions. - Design modern data models and analytics architectures using PySpark, SQL, and Fabric-native services. - Lead technical decision-making, architecture reviews, and risk management throughout project delivery. Partner with Clients: - Lead discovery sessions, architecture workshops, and solution design discussions. - Translate business requirements into practical, scalable technical solutions. - Develop architecture recommendations, effort estimates, staffing recommendations, and delivery approaches. - Present technical strategies, tradeoffs, costs, and recommendations to business, technical, and executive stakeholders. - Help clients define data and analytics roadmaps that support long-term business objectives. Build Trusted Data Foundations: - Architect secure, governed data platforms that support reporting, analytics, automation, and AI initiatives. - Design solutions using Microsoft Fabric, Power BI, Databricks, Azure Data Services, and Microsoft Purview. - Establish approaches for data quality, source control, CI/CD, automated testing, deployment, monitoring, cost management, and operational readiness. - Define governance capabilities including data cataloging, lineage, metadata management, classification, and data stewardship. - Optimize solutions for performance, scalability, reliability, and cost efficiency. Enable AI & Innovation: - Design data foundations that support Microsoft Copilot, AI agents, natural-language interfaces, RAG solutions, and intelligent business applications. - Evaluate emerging technologies and AI capabilities when they provide measurable business value. - Use tools such as GitHub Copilot, Claude, and other AI-assisted technologies to improve architecture, documentation, estimation, testing, analysis, and delivery quality. Now Required Qualifications (What You'll Bring Required Qualifications): List: - 8+ years of experience in data architecture, data engineering, analytics engineering, business intelligence, or related disciplines. - Experience leading architecture and technical delivery for client-facing consulting engagements. - Experience designing and delivering Microsoft Fabric, Azure Data Services, Databricks, and modern analytics solutions. - Advanced knowledge of data modeling, dimensional modeling, semantic modeling, Power BI architecture, data integration, modern analytics architecture patterns, and Microsoft Purview. - Experience designing governed and secure data architectures that support trusted reporting, analytics, automation, and AI-enabled solutions. - Experience defining delivery approaches that include CI/CD, automated testing, deployment, monitoring, and operational readiness. - Strong communication and stakeholder management skills, with demonstrated accountability for the technical success of client engagements. Preferred Qualifications: - Microsoft Fabric certification or equivalent demonstrated Fabric architecture experience. - Microsoft Purview experience with data cataloging, lineage, metadata, classification, and governance capabilities. - AI and agent architecture experience, including data foundations supporting Copilots, natural-language interfaces, RAG solutions, and intelligent applications. - Experience modernizing Azure Data Factory, Azure Synapse Analytics, or other legacy analytics solutions. - Data governance, master data management, or enterprise information management experience. - Familiarity with Azure infrastructure, networking, security, private connectivity, and related architecture concepts. - Experience working in consulting or professional services. Additional Differentiators: - Microsoft Certified: Azure Solutions Architect Expert. - Relevant Microsoft Fabric, Power BI, or Microsoft Purview certifications. - Experience modernizing legacy data and reporting solutions into Fabric, Azure-native, Databricks, or hybrid architectures. - Industry experience in Manufacturing, Financial Services, Healthcare & Life Sciences, or State, Local Government & Education (SLED/GCC). Why Quisitive? maybe could be considered About the role? But we already have About the role. Could add a paragraph about company culture but it's not required. Might be considered boilerplate? It's descriptive of company but not boilerplate; it's substantive. Could include as part of About the role or maybe a separate section like "About Quisitive". But we only have allowed sections; we could add to About the role. We need to avoid duplication. The intro already mentions Quisitive; the "Why Quisitive?" paragraph is additional. We could incorporate it into About the role as additional paragraph. Thus About the role will have two paragraphs: first intro, second why Quisitive. Now Skills section: we could list technical skills extracted from responsibilities and qualifications. But we must not invent; we can list them as they appear. Could create a
  with items like Microsoft Fabric, Azure Data Services, Databricks, Power BI, Microsoft Purview, PySpark, SQL, etc. However many of these are already mentioned in responsibilities/qualifications; listing them again might be duplication but allowed as long as we preserve info. The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." Duplication is okay as long as we don't lose info. But we might be better to not create Skills if it's just repeating. However we need to decide if we include Skills section. The posting does not have a explicit "Skills" heading, but we can infer skills from content. The instruction says: "Use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It suggests we may include Skills if there is real specific content. The posting does mention many specific technologies and abilities; we could treat them as skills. So we can create a Skills section listing them. We must avoid filler like "commensurate with experience". Not present. Now we need to output only HTML fragment, no markdown fences. Let's craft:

  About the role

  Build Modern Data Platforms That Drive Business Outcomes At Quisitive, we help organizations turn data into a strategic asset. As a Data Solutions Architect, you will lead the design and delivery of modern analytics solutions using Microsoft Fabric, Azure Data Services, Power BI, Microsoft Purview, and Databricks. You will partner with clients and delivery teams to architect scalable, secure data platforms that improve reporting, analytics, automation, and AI readiness. This is a client-facing leadership role where you will guide organizations through discovery, solution design, architecture, estimation, and delivery while serving as the technical lead for data and analytics engagements.

  At Quisitive, you will work alongside experienced Microsoft consultants to help clients solve complex business challenges through data, analytics, cloud, and AI technologies. We invest in continuous learning, collaboration, and technical excellence, giving you the opportunity to grow your expertise while making a meaningful impact for our clients.

  Responsibilities

  • Own the technical architecture and solution direction for client engagements.
  • Design Microsoft Fabric, Azure, Databricks, and hybrid analytics platforms aligned with business goals, scalability, governance, and cost requirements.
  • Architect data integration, Lakehouse, data warehouse, semantic modeling, Power BI, and self-service analytics solutions.
  • Design modern data models and analytics architectures using PySpark, SQL, and Fabric-native services.
  • Lead technical decision-making, architecture reviews, and risk management throughout project delivery.
  • Lead discovery sessions, architecture workshops, and solution design discussions.
  • Translate business requirements into practical, scalable technical solutions.
  • Develop architecture recommendations, effort estimates, staffing recommendations, and delivery approaches.
  • Present technical strategies, tradeoffs, costs, and recommendations to business, technical, and executive stakeholders.
  • Help clients define data and analytics roadmaps that support long-term business objectives.
  • Architect secure, governed data platforms that support reporting, analytics, automation, and AI initiatives.
  • Design solutions using Microsoft Fabric, Power BI, Databricks, Azure Data Services, and Microsoft Purview.
  • Establish approaches for data quality, source control, CI/CD, automated testing, deployment, monitoring, cost management, and operational readiness.
  • Define governance capabilities including data cataloging, lineage, metadata management, classification, and data stewardship.
  • Optimize solutions for performance, scalability, reliability, and cost efficiency.
  • Design data foundations that support Microsoft Copilot, AI agents, natural-language interfaces, RAG solutions, and intelligent business applications.
  • Evaluate emerging technologies and AI capabilities when they provide measurable business value.
  • Use tools such as GitHub Copilot, Claude, and other AI-assisted technologies to improve architecture, documentation, estimation, testing, analysis, and delivery quality.