Enterprise Data Architect

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    "datePosted": "2026-05-14T04:00:00.000Z",
    "description": "<h2>Subsidiary</h2>Steel Dynamics\n<h2>Overview</h2>\n<p>The Enterprise Data Architect is the technical cornerstone of Steel Dynamics' enterprise data platform initiative. This newly created role will lead the design and build-out of a company-wide data platform that will serve as SDI's first foundation for enterprise reporting, analytics, and AI/ML.</p>\n<p> </p>\n<p>SDI is a highly decentralized organization. Divisions own their source systems and operate with significant autonomy. The Enterprise Data Architect must be equally comfortable working independently to drive the architecture forward and collaboratively to bring divisions along. The role requires earning trust across divisions rather than relying on positional authority.</p>\n<p> </p>\n<p>This role begins as a senior individual contributor with significant build-out responsibility, and is expected to evolve as the platform matures and the enterprise data function grows. The strongest candidates will be excellent as both architects and builders.</p>\n<p> </p>\n<p><strong>What Makes This Role Distinctive</strong></p>\n<ul>\n <li>Greenfield enterprise platform with growth trajectory. This is a build-from-the-ground-up opportunity. Architectural choices made in this role will shape SDI's data foundation for the next decade, and the role is structured to evolve as the platform matures and the enterprise data function grows.</li>\n <li>Real architectural authority. SDI has not locked in technology commitments for this platform. The Enterprise Data Architect's recommendations on platform, tooling, and standards will drive the decisions.</li>\n <li>Builder-leader trajectory. This role is positioned to play a central part in shaping and growing SDI's enterprise data engineering capability over time.</li>\n <li>A culture that moves fast when aligned. SDI is decentralized, but when we align, we move with surprising speed. A successful architect here will see their designs translated into operating reality faster than in most enterprise environments.</li>\n</ul>\n<p><strong>About Steel Dynamics, Inc.</strong></p>\n<p>Steel Dynamics is one of the largest domestic steel producers and metals recyclers in North America, with approximately 15,000 employees and operations spanning steelmaking, steel fabrication, metals recycling, aluminum, and biocarbon. SDI's culture is built on entrepreneurial spirit, decentralized decision-making, accountability, and aligned long-term interests across all stakeholders. We are committed to safety, operational excellence, and continuous innovation.</p>\n<h2>Responsibilities</h2>\n<ul>\n <li>Lead the design and build-out of the enterprise data platform, including platform selection, reference architecture, and the standards and patterns the platform will operate on.</li>\n <li>Define the architecture for moving data from divisional source systems — predominantly on-premises SQL Server — into the cloud-hosted platform, including ingestion, security, and reliability.</li>\n <li>Establish enterprise data engineering standards governing the corporate-owned platform.</li>\n <li>Partner with divisional IT teams on integrating division data into the platform, providing architectural guidance and technical support without taking ownership of divisional data away from the divisions.</li>\n <li>Provide hands-on data engineering support to divisions that do not yet have dedicated data engineering capability; transition this work to a growing team as the function scales.</li>\n <li>Design the security, governance, and access-control model for the platform.</li>\n <li>Architect the platform to support enterprise AI and machine learning workloads.</li>\n <li>Define environment, CI/CD, cost management, and operational monitoring approaches for the platform.</li>\n <li>Serve as the senior technical voice in vendor evaluations, proof-of-concept work, and platform decisions.</li>\n <li>Mentor divisional data engineers and analysts working within the platform.</li>\n <li>Communicate clearly with non-technical executive stakeholders, translating architectural choices into business outcomes, risks, and trade-offs.</li>\n</ul>\n<h2>Qualifications</h2>\n<p><strong>Required</strong></p>\n<ul>\n <li>10+ years of progressive experience implementing large-scale software systems in production enterprise environments.</li>\n <li>5+ years experience in data engineering, data warehousing, and/or data architecture in production environments.</li>\n <li>Demonstrated experience leading and personally owning the design and delivery of at least one greenfield or major-overhaul enterprise data platform spanning multiple business units, source systems, or geographies.</li>\n <li>Demonstrated experience designing hybrid cloud / on-premises data architectures, including secure and reliable movement of data from on-premises source systems into cloud platforms.</li>\n <li>Working proficiency across multiple cloud data platforms sufficient to lead a credible platform evaluation and make defensible recommendations.</li>\n <li>Strong familiarity with the Microsoft data and analytics ecosystem.</li>\n <li>Strong technical foundation across SQL, a general-purpose programming language used in data engineering, modern data engineering practices, and data warehousing fundamentals.</li>\n <li>Experience integrating data from heterogeneous source systems in a multi-business-unit environment, including ERP and operational systems.</li>\n <li>Working knowledge of data security, governance, and compliance frameworks sufficient to architect compliant data platforms.</li>\n <li>Excellent written and verbal communication skills, with proven ability to present architectural concepts and trade-offs to both technical teams and non-technical executive stakeholders.</li>\n <li>Demonstrated ability to work effectively in a decentralized organizational structure — building consensus, earning trust, and driving outcomes through influence rather than authority.</li>\n <li>Bachelor's degree in a relevant field, or equivalent professional experience.</li>\n</ul>\n<p><strong>Preferred</strong></p>\n<ul>\n <li>Experience designing data platforms in manufacturing, metals, industrial, or other heavy-asset industries.</li>\n <li>Experience integrating MES, historian, and shop-floor data alongside ERP and financial data.</li>\n <li>Experience architecting data platforms that support AI/ML and large language model workloads.</li>\n <li>Experience leading or mentoring distributed data engineering teams.</li>\n <li>Experience establishing data governance practices in decentralized, multi-business-unit organizations.</li>\n</ul>\n<p><em><strong>Steel Dynamics, Inc., and all affiliated entities are equal opportunity employers. </strong></em></p>",
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