Data Architect
Madison-Davis, LLC
A leading enterprise organization is seeking an experienced Enterprise Data Architect to help define and modernize its next-generation data platform strategy. This is a highly visible, hands‑on architecture role responsible for designing scalable cloud data platforms, establishing enterprise architecture standards, and enabling modern analytics and Artificial Intelligence capabilities across the organization. The ideal candidate combines strategic architecture leadership with practical implementation experience and enjoys collaborating across engineering, governance, cybersecurity, compliance, and business teams. What You'll Tackle: Define enterprise data architecture strategy, roadmaps, standards, and target‑state architectures. Design secure, scalable cloud‑based data platforms supporting analytics, governance, AI, and enterprise reporting. Lead architecture initiatives across modern data ecosystems, including lakehouse platforms, orchestration, data warehousing, business intelligence, and distributed processing. Establish enterprise standards for data modeling, metadata, lineage, semantic layers, integration architecture, and data lifecycle management. Design AI‑ready data architectures supporting semantic modeling, metadata‑driven frameworks, vector‑enabled architectures, and scalable enterprise data pipelines. Partner with governance, cybersecurity, risk, compliance, and legal teams to ensure privacy, security, retention, auditability, and regulatory alignment. Review enterprise architecture designs to ensure consistency with architecture standards and security principles. Provide technical leadership by translating complex architectural concepts into practical business recommendations. What You Bring: Extensive experience in Enterprise Data Architecture, Solution Architecture, Data Engineering, or Data Platform Modernization. Strong experience with modern cloud data ecosystems, including: Cloud Data Lakes, Data Warehousing, Lakehouse Architectures, Distributed Data Processing, and Enterprise Analytics Platforms. Deep understanding of: Data Modeling, Metadata Management, Data Lineage, Data Governance, Master & Reference Data, Integration Architecture, and Data Lifecycle Management. Experience supporting AI/ML data architectures including AI-ready pipelines, semantic modeling, feature engineering, and analytical data environments. Experience with enterprise architecture and governance tools such as: Erwin, ER/Studio, Collibra, Microsoft Purview, Alation, Visio, Lucidchart, or similar platforms. Familiarity with: APIs, Event-Driven Architecture, Data Mesh, Data Fabric, Distributed Processing. Experience supporting enterprise data quality, security, privacy, access governance, auditability, and regulatory compliance. Strong communication skills with the ability to influence both technical and business stakeholders. #J-18808-Ljbffr Madison-Davis, LLC
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