Enterprise Data Architect

TEKsystems•Spring, TX

21h•$90 - $105•Hybrid

About The Position

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.

Requirements

12+ years designing enterprise-scale data architectures, governance frameworks, data ownership models, stewardship, and data lifecycle management.
Expertise in data cataloging, lineage, classification, labeling, metadata management, and establishing visibility into where data originates, moves, and is consumed.
Hands-on experience implementing Microsoft Purview, sensitivity labels, information protection, DLP, data discovery, and governance controls across the enterprise.
Experience preparing enterprise data for AI consumption, with strong knowledge of Azure, Databricks, Oracle Databases, data quality, segmentation, and trusted dataset governance.
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.
Combines deep technical architecture expertise with executive-level leadership, governance, and organizational change management capabilities.
Data architecture
data governance
data classification
data lineage
information protection
microsoft purview

Nice To Haves

Experience preparing organizations for AI, Generative AI, Machine Learning, or Copilot implementations.
Experience with Microsoft Fabric.
Experience working within highly regulated industries.
Azure, Databricks, Oracle, Data Governance, or Enterprise Architecture certifications.
Familiarity with NIST, ISO 27001, DAMA-DMBOK, DCAM, and AI governance frameworks.

Responsibilities

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.
Establish enterprise-wide data governance frameworks, policies, standards, and operating models.
Define and implement data ownership, stewardship, accountability, and governance processes.
Establish enterprise metadata management and data cataloging programs.
Develop governance standards for data quality, retention, auditing, and lifecycle management.
Create governance processes ensuring enterprise data remains accurate, trusted, and reusable.
Build governance models that align business, technology, compliance, and security requirements.
Design and implement enterprise data classification frameworks.
Define sensitivity classifications for public, internal, confidential, restricted, regulated, and business-critical information.
Establish data labeling standards using Microsoft Purview and Microsoft Information Protection capabilities.
Ensure data classification policies are consistently applied across enterprise repositories.
Develop governance standards for data handling, storage, access, and sharing based on classification levels.
Define enterprise policies for information protection and secure data consumption.
Establish enterprise visibility into data lineage, provenance, ownership, and usage.
Implement comprehensive metadata management and data catalog solutions using Microsoft Purview.
Create enterprise data inventories that provide transparency into data assets across Azure, Oracle, Databricks, and business applications.
Ensure traceability of enterprise data from source systems through downstream analytics and AI solutions.
Develop standards for business glossary, taxonomy, metadata, and data documentation.
Design enterprise data segmentation strategies that appropriately separate sensitive and regulated information.
Establish governance controls governing access to enterprise data assets.
Define standards for role-based and attribute-based access controls.
Partner with cybersecurity teams to align data architecture with Zero Trust principles.
Ensure sensitive enterprise data is isolated, protected, and accessible only to authorized users and systems.
Lead the organization's AI data readiness strategy and maturity roadmap.
Define requirements for trusted datasets approved for AI, machine learning, and generative AI consumption.
Establish standards for dataset quality, lineage, classification, transparency, and governance.
Ensure enterprise AI initiatives consume properly classified and governed information assets.
Develop architectural guardrails for AI, Copilot, Agentic AI, retrieval systems, vector databases, and knowledge repositories.
Partner with Data Science, Analytics, and Architecture teams to prepare enterprise data assets for responsible AI adoption.
Lead the design and implementation of Microsoft Purview as the enterprise governance platform.
Drive enterprise adoption of: Data Catalog, Data Map, Data Lineage, Information Protection, Sensitivity Labels, Data Loss Prevention (DLP), Data Lifecycle Management, Compliance and Governance Controls.
Establish governance processes supporting automated data discovery, classification, and protection.
Establish architectural standards across Microsoft Azure, Databricks, Oracle Fusion, and Oracle database environments.
Design enterprise data integration and governance patterns across cloud and business application ecosystems.
Develop standards governing enterprise data pipelines, lakehouses, warehouses, and operational systems.
Partner with platform engineering teams to ensure governance controls are embedded within enterprise data platforms.
Ensure enterprise architecture standards support scalability, security, resiliency, and AI enablement.
Serve as the enterprise thought leader for data architecture and governance.
Influence executive leaders on data strategy, AI readiness, governance investments, and risk management.
Lead enterprise workshops, architecture reviews, governance councils, and steering committees.
Mentor architects, engineers, data stewards, and governance teams.
Drive organizational adoption of enterprise data standards and governance practices.