Sr. Fabric Technical Data Architect at Hermanson Company
Worldwide
$165k - $195k
<p><strong>Hermanson Company</strong> is a standout Mechanical company that has been doing business in the Puget Sound area since 1979. Over the last four decades we have grown from a family owned sheet metal contractor to a partner led full service mechanical construction, design and maintenance provider playing a significant role in the U.S. national construction industry. </p> <p>By design, Hermanson is a special place to work. Our belief is that people do business with people they like. In keeping with that belief, we strive to hire and retain highly motivated people who are professional, ethically unwavering, and unrelenting in delivering quality results. We are focused on providing a workplace where high performance individuals come together to build dedicated teams driven to accomplish great things for our customers.</p> <p>People love working at Hermanson, because we all share the same Core Values:</p> <ul> <li><strong>Clients First </strong>– Caring, win-win, value, quality and service attitude </li> <li><strong>Family Matters</strong> - Safety, wellness, stability, enjoyment and balance</li> <li><strong>Character Matters</strong> – Integrity, accountability, passionate, and caring</li> <li><strong>Team</strong> - Trust, honesty, respect, reliable and inclusive</li> <li><strong>Appreciate</strong> – Each other, our successes, and enjoy the journey</li> <li><strong>Learn, Grow, Innovate</strong> – Challenge the status quo and always compete</li> </ul> <p><span style="font-size: 14pt;"><strong>The Role</strong></span></p> <p>The Sr. Fabric Technical Data Architect reports to the CIO, in the IT Department. This role is responsible for designing, building, and operationalizing the company’s Microsoft Fabric-based data platform and lakehouse architecture.</p> <p>This role owns the technical execution layer of the enterprise data program, translating business data models into scalable, governed, and high-performing solutions. It works in close partnership with the Sr. Data & Solutions Architect, who owns the business information model, data strategy, and the definitions of what the data means. This role owns how that model is built and run: the platform architecture, pipelines, governance, and operations that bring it to life. Together, this partnership is critical to evolving from an MVP data platform to a sustainable, in-house enterprise data capability supporting reporting, analytics, and future AI initiatives.</p> <p><span style="font-size: 14pt;"><strong>Responsibilities</strong></span></p> <p><strong>Fabric Platform Architecture</strong></p> <ul> <li>Design and manage end-to-end Microsoft Fabric architecture, including: Lakehouse structure (Bronze / Silver / Gold); Workspace and environment strategy (Dev / UAT / Prod); and Data integration and orchestration patterns</li> <li>Define and enforce technical standards for scalability, performance, and cost efficiency</li> <li>Establish architectural roadmaps aligned to analytics and business objectives</li> </ul> <p><strong>Data Engineering & Integration</strong></p> <ul> <li>Build and maintain data ingestion pipelines across systems (D365 F&O, CRM, Fabrication, Service, etc.)</li> <li>Implement transformation logic to produce curated, reporting and analytics-ready datasets</li> <li>Establish consistent patterns for moving data from source → lakehouse → semantic layer in batch, streaming, and real-time patterns</li> <li>Ensure alignment between technical models and the defined business information model</li> <li>Enable reliable, performant datasets for Power BI and downstream analytics</li> </ul> <p><strong>Governance, Security & Operations</strong></p> <ul> <li>Establish and enforce data governance frameworks, including: data quality standards; metadata and cataloging; and lineage and observability</li> <li>Define and manage security and access controls across data platform components</li> <li>Support evolution toward a formal data governance and ownership model</li> </ul> <p><strong>DevOps & Delivery</strong></p> <ul> <li>Own deployment pipelines, CI/CD processes, and release management for Fabric</li> <li>Enable structured incremental delivery supporting testing, UAT, and production stabilization</li> </ul> <p><strong>Platform Expansion & Future Readiness</strong></p> <ul> <li>Expand the platform beyond core ERP data into additional enterprise systems</li> <li>Ensure data architecture is AI-ready (clean, governed, accessible)</li> <li>Continuously optimize for performance, cost, and usability</li> <li>Evaluate and recommend new technologies and tools aligned with strategic direction</li> </ul> <p>The salary range for this position is $165,000 to $195,000. <em>(The compensation offered may vary depending on job-related knowledge, skills and experience).</em></p> <p><span style="font-size: 14pt;"><strong>Qualifications</strong></span></p> <p><strong>Preferred Qualifications</strong></p> <ul> <li>Background in industries with complex operational data (construction, fabrication, or project-based environments)</li> <li>Experience with:</li> <ul> <li>Supporting analytics, reporting, and AI use cases</li> <li>Semantic modeling and analytics platforms (e.g., Power BI)</li> <li>Data cataloging, lineage, and metadata management tools</li> </ul> <li>Exposure to AI/ML data platform design or analytics enablement</li> <li>Experience leading or mentoring technical teams</li> <li>Ability to operate effectively in MVP → scale/maturity transitions</li> </ul> <p><strong>What Success Looks Like (First 6-12 Months)</strong></p> <ul> <li>Stabilizes and operationalizes the existing Fabric Data Lakehouse (V1)</li> <li>Establishes clear architecture standards, patterns, and repeatable processes</li> <li>Successfully delivers incremental V2 capabilities aligned to business priorities</li> <li>Transitions key platform capabilities from external partners to a sustainable in-house model</li> <li>Provides consistent, reliable datasets enabling: trusted reporting, faster data access for business users, and readiness for future AI initiatives</li> </ul> <p><span style="font-size: 14pt;"><strong>Education</strong></span></p> <p>Bachelor's degree (B. S.) in Software Engineering, Computer Science, Information Systems, Data Science, Mathematics, from a four-year college or university or equivalent combination of technical training and/or related field experience.</p> <p><strong>Hermanson offers a comprehensive benefits package designed to support your health, financial future, and professional growth.</strong></p> <ul> <li>Competitive pay with bonus opportunities</li> <li>Medical, prescription, dental & vision coverage with zero to low weekly premiums</li> <li>401(k) with discretionary company match</li> <li>Generous paid time off (vacation, sick time, and paid holidays)</li> <li>Disability income protection</li> <li>Life insurance for employees and eligible dependents</li> <li>Optional added protection with critical illness and accident plans</li> <li>Career growth & development opportunities</li> <li>In-house training programs</li> <li>Certificate & tuition reimbursement</li> <li>Wellness program</li> <li>Employee Assistance Program (EAP)</li> </ul> <p><span style="font-size: 14pt;"><strong><em>This position is not eligible for employment visa sponsorship.</em></strong></span></p> <p><em>Hermanson company LLC is proud to be an Equal Opportunity Employer. Hermanson does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit and business need.</em><strong> </strong></p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p>The pay range for this position may vary depending on job-related knowledge, skills and experience.</p></div><div class="title">WA Residents</div><div class="pay-range"><span>$165,000</span><span class="divider">—</span><span>$195,000 USD</span></div></div></div>
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