Salesforce Developer

Cyber Security Data Discovery Data Pipelines Responsible AI Loss Prevention Microsoft Azure Data Governance Vector Database Azure Databricks Oracle Databases Data Integration Machine Learning Data Engineering Data Sovereignty Business Software Data Architecture Data Segmentation Intelligent Agent Advanced Analytics Business Valuation Thought Leadership Metadata Management Data Classification Business Leadership Lifecycle Management Business Technologies Packaging And Labeling Full Stack Development Enterprise Architecture Application Development Business Transformation Oracle Fusion Middleware Information Architecture Product Family Engineering Organizational Change Management Generative Artificial Intelligence, 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.

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.

Data Classification, Labeling & Information Protection

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.

Data Lineage, Cataloging & Metadata Management

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.

Data Segmentation & Access Governance

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.

AI Data Readiness

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.

Microsoft Purview Strategy & Governance

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.

Azure, Databricks & Oracle Data Platform Governance

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.

Leadership & Stakeholder Management

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., Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools. Related Jobs Enterprise Data Architect TEKsystems

Spring, TX*Remote

Auditing Equities Metadata Taxonomy Operations Leadership Automation Governance Resilience Databricks Agentic AI Warehousing Scalability AI Adoption Data Quality Data Science Data Lineage Data Security Data Strategy ISO/IEC 27001 Data Labeling Accountability Cyber Security Data Discovery Data Pipelines Responsible AI Loss Prevention Microsoft Azure Data Governance Vector Database Azure Databricks Oracle Databases Data Integration Machine Learning Data Engineering Data Sovereignty Business Software Data Architecture Data Segmentation Intelligent Agent Advanced Analytics Business Valuation Thought Leadership Metadata Management Data Classification Business Leadership Lifecycle Management Business Technologies Packaging And Labeling Full Stack Development Enterprise Architecture Application Development Business Transformation Oracle Fusion Middleware Information Architecture Product Family Engineering Organizational Change Management Generative Artificial Intelligence

Equities Metadata Taxonomy Operations Leadership Automation Governance Resilience Databricks Agentic AI Warehousing Scalability AI Adoption Data Quality Data Science Data Lineage Data Security Data Strategy ISO/IEC 27001 Data Labeling, 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., Data architecture, data governance, data classification, data lineage, information protection, microsoft purview

Top Skills Details

Data architecture,data governance,data classification,data lineage,information protection

Additional Skills & Qualifications

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., Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors.

We’re partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That’s the power of true partnership. TEKsystems is an Allegis Group company., We’re a leading provider of business and technology services. We accelerate business transformation for our customers. Our expertise in strategy, design, execution and operations unlocks business value through a range of solutions. We’re a team of 80,000 strong, working with over 6,000 customers, including 80% of the Fortune 500 across North America, Europe and Asia, who partner with us for our scale, full-stack capabilities and speed. We’re strategic thinkers, hands-on collaborators, helping customers capitalize on change and master the momentum of technology. We’re building tomorrow by delivering business outcomes and making positive impacts in our global communities. TEKsystems and TEKsystems Global Services are Allegis Group companies. Learn more at TEKsystems.com.