Enterprise Data Architect

This role is 3 days on site in Spring, Texas and contract to hire. Top Skills' Details The ideal candidate has a background in data engineering -> Data Architecture -> At least 1-2 projects in setting up an AI Ready Data Ecosystem Enterprise Data Architecture & Governance 12+ years designing enterprise-scale data architectures, governance frameworks, data ownership models, stewardship, and data lifecycle management.

Data Classification, Lineage & Metadata Management Expertise in data cataloging, lineage, classification, labeling, metadata management, and establishing visibility into where data originates, moves, and is consumed. Microsoft Purview & Information Protection Hands-on experience implementing Microsoft Purview, sensitivity labels, information protection, DLP, data discovery, and governance controls across the enterprise.

AI Data Readiness & Modern Data Platforms Experience preparing enterprise data for AI consumption, with strong knowledge of Azure, Databricks, Oracle Databases, data quality, segmentation, and trusted dataset governance. Description *6 Month Contract To Hire* Ideal Candidate Profile A transformational Data Architect who has previously built enterprise-grade data governance and information architecture programs, implemented data cataloging and lineage at scale, established classification and stewardship frameworks, and successfully prepared a large organization's data estate for AI consumption.

This individual combines deep technical architecture expertise with executive-level leadership, governance, and organizational change management capabilities. Position Summary The Principal Enterprise Data Architect is responsible for establishing and executing the enterprise data architecture strategy required to enable secure, governed, and scalable AI adoption across the organization. This role will serve as the enterprise authority for data architecture, data governance, data classification, metadata management, data lineage, information protection, data segmentation, and AI data readiness.

The architect will lead the transformation of the organization's data landscape to ensure enterprise information is discoverable, trusted, appropriately governed, and ready for consumption by advanced analytics, machine learning, generative AI, intelligent agents, and future AI-driven business capabilities. The successful candidate will design and implement the enterprise framework that provides visibility into what data exists, where it originates, how it moves throughout the organization, who owns it, who has access to it, and how it should be classified, protected, and governed throughout its lifecycle.

This individual will partner closely with Enterprise Architecture, Cybersecurity, Data & Analytics, Infrastructure, Application Development, Risk, Compliance, Legal, and Business Leadership teams to establish the organization's "gold standard" for enterprise data architecture and AI readiness. Key Responsibilities: Enterprise Data Architecture Define and execute the enterprise data architecture strategy and roadmap.

Establish enterprise standards for data architecture, metadata management, data integration, data lifecycle management, and information governance. Create reference architectures for Azure, Databricks, Oracle Fusion, Oracle databases, and enterprise data platforms. Design scalable data architectures that support analytics, reporting, machine learning, generative AI, and future AI initiatives. Develop architectural standards governing structured, semi-structured, and unstructured enterprise data.

Lead enterprise architecture reviews for strategic data initiatives and platform investments. Serve as the enterprise subject matter expert for data architecture best practices. Data Governance & Data Management Establish enterprise-wide data governance frameworks, policies, standards, and operating models. Define and implement data ownership, stewardship, accountability, and governance processes.

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