Enterprise Data Architect, Microsoft Fabric

We need to produce HTML fragment with sections: About the role? Actually the posting includes description of company and role. We need to use

for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title as heading. Must not include Job ID/requisition numbers as headings; fold minor metadata into short

or drop it. Remove boilerplate (cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions). Preserve all substantive information. We need to parse the posting: First paragraph: company description. Could be "About the role"? Actually that's about company. Might be "About the role" or "About Sealed Air". The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can have "About the role" heading for the description of what you will do? The posting includes "What will you do as a Principal Enterprise Data Architect, Microsoft Fabric at Sealed Air?" That's responsibilities. Then "Why do we need you?" also responsibilities. Then "What do you need to succeed?" includes Required Qualifications and Preferred Qualifications. Also there is "Requisition id: 55324 Relocation: Yes" - minor metadata, we can put in a short

maybe under a generic section? But we should not create a heading for it. Could embed in a

after sections. We need to avoid duplication: there is duplicate line "c10+ years of experience..." appears duplicated? Actually there is a line: "c10+ years of experience in data architecture, data engineering, or analytics, with experience leading complex enterprise solutions." Looks like a typo with leading c. It's duplicate of required qualification line. We should preserve but not duplicate? The instruction: Preserve ALL substantive information; do NOT invent or summarize away detail. Remove duplicated lines. So we should keep only one instance of that line. We need to remove boilerplate: EEO statements, fraud warning, etc. Also remove "Please be cautious of fraudulent recruiting efforts..." etc. Also remove "LINK1 MON1" at end. We need to keep relocation info? It's minor metadata; we can include in a short

maybe after sections. We need to not create Pay/Schedule/Benefits sections unless posting actually states them. There is no mention of pay, benefits, schedule. So we omit those sections. We need to include sections only when posting has real specific content. So we will have:

About the role

maybe containing company description? Or we could put company description under About the role? The instruction: "Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." So we can use About the role for an overview of the role and company. Then Responsibilities for what you will do. Then Requirements maybe for required qualifications? But they also have Qualifications heading. The list includes both Requirements and Qualifications. We need to decide which to use. Could combine Required Qualifications under Requirements, and Preferred Qualifications under Qualifications. Or we could have Requirements for required, Qualifications for preferred. That seems logical. Skills: maybe we can list specific skills like Microsoft Fabric expertise, data modeling, etc. But we already have qualifications covering that. Could create Skills section for technical skills: Microsoft Fabric, OneLake, Lakehouse/Warehouse, pipelines, Spark, Power BI, semantic models, data modeling, medallion architecture, enterprise integration, metadata, lineage, security, governance, cloud data platforms, generative AI/ML, Azure AI services, Azure OpenAI, Microsoft Copilot, Fabric Data Science, React, APIs, SAP, Salesforce, certifications. But we must not invent; we can extract from posting. Let's extract substantive content: Company description: "Sealed Air designs and delivers packaging solutions that protect essential goods transported worldwide, preserve food, enable e-commerce and digital connectivity, and help create a global supply chain that is touchless, safer, less wasteful, and more resilient. We strive to foster a caring, high-performance growth culture that will deliver consistent, sustainable profitable growth and accelerate our performance – a culture where accountability is clear and aligned, and where we reward business outcomes and impact. That culture guides everything we do, including how we partner with our customers and suppliers, how we attract and retain top talent, and how we create and deliver value to our stakeholders. In 2025, Sealed Air generated $5.4 billion in sales and has approximately 16,100 employees who serve customers in 119 countries/territories. To learn more, visit www.sealedair.com." That's about the company; could be placed under About the role. Responsibilities: "What will you do as a Principal Enterprise Data Architect, Microsoft Fabric at Sealed Air? We are modernizing how data is delivered across the enterprise, with Microsoft Fabric serving as the foundation for analytics, digital products, and AI. We are looking for a Principal Enterprise Data Architect to lead that architecture and help turn the strategy into working solutions. This is a senior, hands-on role for someone who can set direction, make pragmatic decisions, and stay engaged through delivery. You will help build trusted, reusable data products that support Power BI, business applications, and emerging AI use cases. The right candidate combines strong Microsoft Fabric expertise with sound enterprise architecture judgment and the ability to lead through influence across global teams." Then "Why do we need you?" bullet list: - Set the architecture and technical direction for our Microsoft Fabric platform. - Define practical, reusable patterns for data ingestion, transformation, Lakehouse and Warehouse design, data modeling, semantic models, security, and governance. - Ensure trusted data and business logic can be reused across Power BI, React-based applications, APIs, and AI solutions. - Build an AI-ready data foundation with the quality, metadata, lineage, context, and controls needed for generative AI and machine learning use cases. - Guide the modernization of legacy data platforms into Microsoft Fabric while balancing delivery speed, reliability, performance, and cost. - Partner with data, application, security, architecture, and business teams from solution design through production. - Mentor engineers, review key designs, and communicate architecture decisions and tradeoffs clearly to technical teams and senior leaders. That's responsibilities. Required Qualifications (list): - 10+ years of experience in data architecture, data engineering, or analytics, with experience leading complex enterprise solutions. - Strong hands-on experience with Microsoft Fabric, including OneLake, Lakehouse or Warehouse, pipelines, Spark, Power BI, and semantic models. - Strong knowledge of data modeling, medallion architecture, enterprise integration, metadata, lineage, security, and governance. - Experience designing cloud data platforms that serve reporting, analytics, APIs, or modern applications. - Working knowledge of how enterprise data supports generative AI and machine learning, including secure access, grounding, and retrieval. - Ability to move between strategy and implementation and communicate effectively with engineers, business partners, and senior leaders. Note there is a duplicate line "c10+ years of experience..." we will keep only one. Preferred Qualifications: - Experience with Azure AI services, Azure OpenAI, Microsoft Copilot, or Fabric Data Science. - Experience supporting React or other modern applications through APIs or embedded analytics. - Experience integrating or modernizing data from SAP, Salesforce, or other large enterprise platforms. - Relevant Microsoft Fabric, Azure architecture, data engineering, or AI certification. Also there is "Requisition id: 55324 Relocation: Yes" - we can put in a short

maybe after sections. We must not include boilerplate: EEO statements, fraud warning, etc. Now produce HTML fragment:

About the role

Sealed Air designs and delivers packaging solutions that protect essential goods transported worldwide, preserve food, enable e-commerce and digital connectivity, and help create a global supply chain that is touchless, safer, less wasteful, and more resilient. We strive to foster a caring, high-performance growth culture that will deliver consistent, sustainable profitable growth and accelerate our performance – a culture where accountability is clear and aligned, and where we reward business outcomes and impact. That culture guides everything we do, including how we partner with our customers and suppliers, how we attract and retain top talent, and how we create and deliver value to our stakeholders. In 2025, Sealed Air generated $5.4 billion in sales and has approximately 16,100 employees who serve customers in 119 countries/territories. To learn more, visit www.sealedair.com.

Responsibilities

• We are modernizing how data is delivered across the enterprise, with Microsoft Fabric serving as the foundation for analytics, digital products, and AI. We are looking for a Principal Enterprise Data Architect to lead that architecture and help turn the strategy into working solutions. This is a senior, hands-on role for someone who can set direction, make pragmatic decisions, and stay engaged through delivery. You will help build trusted, reusable data products that support Power BI, business applications, and emerging AI use cases. The right candidate combines strong Microsoft Fabric expertise with sound enterprise architecture judgment and the ability to lead through influence across global teams.
• Set the architecture and technical direction for our Microsoft Fabric platform.
• Define practical, reusable patterns for data ingestion, transformation, Lakehouse and Warehouse design, data modeling, semantic models, security, and governance.
• Ensure trusted data and business logic can be reused across Power BI, React-based applications, APIs, and AI solutions.
• Build an AI-ready data foundation with the quality, metadata, lineage, context, and controls needed for generative AI and machine learning use cases.
• Guide the modernization of legacy data platforms into Microsoft Fabric while balancing delivery speed, reliability, performance, and cost.
• Partner with data, application, security, architecture, and business teams from solution design through production.
• Mentor engineers, review key designs, and communicate architecture decisions and tradeoffs clearly to technical teams and senior leaders.

But note the first bullet includes a paragraph; maybe better to separate into

for prose and

for list. The instruction: Use
• for any list of duties/requirements/benefits, and

  for prose. So we should separate prose from list. The responsibilities section includes both prose and list. We can put the introductory prose in a

  , then the bullet list in

  . Thus:

  Responsibilities

  We are modernizing how data is delivered across the enterprise, with Microsoft Fabric serving as the foundation for analytics, digital products, and AI. We are looking for a Principal Enterprise Data Architect to lead that architecture and help turn the strategy into working solutions. This is a senior, hands-on role for someone who can set direction, make pragmatic decisions, and stay engaged through delivery. You will help build trusted, reusable data products that support Power BI, business applications, and emerging AI use cases. The right candidate combines strong Microsoft Fabric expertise with sound enterprise architecture judgment and the ability to lead through influence across global teams.

  • Set the architecture and technical direction for our Microsoft Fabric platform.
  • Define practical, reusable patterns for data ingestion, transformation, Lakehouse and Warehouse design, data modeling, semantic models, security, and governance.
  • Ensure trusted data and business logic can be reused across Power BI, React-based applications, APIs, and AI solutions.
  • Build an AI-ready data foundation with the quality, metadata, lineage, context, and controls needed for generative AI and machine learning use cases.
  • Guide the modernization of legacy data platforms into Microsoft Fabric while balancing delivery speed, reliability, performance, and cost.
  • Partner with data, application, security, architecture, and business teams from solution design through production.
  • Mentor engineers, review key designs, and communicate architecture decisions and tradeoffs clearly to technical