Data Architect

Location: Dallas, TX

Salary: $100.00 USD Hourly - $120.00 USD Hourly

Description: Enterprise Data Architect (Data Platforms, Integration & AI Enablement)

Location: Initial hybrid and then mostly remote/travel for major milestones

Employment Type: Contract

Overview

We are seeking a highly experienced Enterprise Data Architect to define and lead the long-term data architecture strategy for a rapidly growing organization. This individual will be responsible for creating the enterprise data foundation that supports operational reporting, analytics, AI, digital transformation, and future data-driven initiatives across the business.

This role goes beyond traditional data warehousing or business intelligence. The ideal candidate will architect and establish a scalable, modern, cloud-based data ecosystem that integrates enterprise applications, project systems, operational platforms, and future industrial data sources into a single governed architecture.

The successful candidate will combine strategic vision with hands-on technical expertise, helping shape the organization's data future while providing architectural leadership across internal teams and external partners.

• Enterprise Data Strategy & Architecture
• Define and own the enterprise data architecture vision, roadmap, standards, and governance framework.
• Establish a scalable future-state architecture supporting analytics, operational intelligence, AI, and enterprise reporting.
• Create reference architectures, standards, and best practices for enterprise data management.
• Ensure a single source of truth across business functions and eliminate data silos and redundant platforms.
• Serve as the organization's primary authority for enterprise data architecture decisions.
• Modern Data Platform Leadership
• Design and build a cloud-based enterprise data platform capable of integrating data across business, operational, project, and future industrial systems.
• Develop solutions leveraging technologies such as: Databricks, Snowflake, Microsoft Fabric, Azure Data Services.
• Data Lake, Data Warehouse, and Lakehouse architectures
• Establish scalable data ingestion, orchestration, transformation, and storage strategies.
• Ensure architecture remains vendor-agnostic and adaptable to future technologies.
• Integration & Data Engineering Architecture
• Define enterprise integration standards and architecture patterns.
• Lead development of API-first and event-driven integration frameworks.
• Establish scalable ETL/ELT, streaming, orchestration, and data movement strategies.
• Prevent proliferation of point-to-point integrations and disconnected reporting environments.
• Drive enterprise-wide standards for interoperability between platforms and applications.
• Data Governance & Information Management
• Establish enterprise data governance programs and operating models.
• Define ownership, stewardship, lineage, metadata management, and data quality standards.
• Create and maintain master data and reference data strategies.
• Ensure authoritative data sources and governance processes are consistently adopted across the organization.
• Partner with business and technology leaders to improve data reliability and trust.
• AI & Advanced Analytics Enablement
• Build the foundation for next-generation AI, analytics, and digital capabilities.
• Design AI-ready architectures supporting: Machine Learning, Generative AI, Retrieval-Augmented Generation (RAG), Vector-based architectures, Unstructured data management, Enterprise knowledge systems.
• Support development of secure agentic AI environments by enabling governed data products, semantic layers, APIs, and enterprise knowledge access.
• Establish responsible AI data architecture practices and governance controls.
• Security, Risk & Compliance
• Partner closely with Cybersecurity, Legal, Compliance, and Technology teams.
• Define standards for: Data security, Access governance, Privacy controls, Data retention, Regulatory compliance, Responsible AI usage.
• Ensure enterprise architecture aligns with security and risk-management requirements.
• Technical Leadership
• Provide architectural leadership for enterprise initiatives and strategic programs.
• Guide implementation teams, system integrators, and technology partners.
• Evaluate platforms, technologies, and architectural approaches.
• Maintain organizational ownership of data models, integration standards, governance frameworks, and long-term platform direction.
• Remain hands-on enough to prototype solutions, troubleshoot issues, and provide technical oversight when necessary.

Required Qualifications

• 10+ years of progressive experience in data architecture, enterprise architecture, data engineering, or platform architecture.
• Experience designing and implementing enterprise-scale data platforms.
• Strong expertise with modern cloud data technologies such as Databricks, Snowflake, Microsoft Fabric, Azure Data Services, or similar platforms.
• Extensive experience with: Data Lakes, Lakehouse Architectures, Data Warehouses, ETL/ELT Frameworks, APIs, Event-Driven Architectures, Enterprise Integration Patterns.
• Proven success establishing enterprise data governance frameworks.
• Strong understanding of metadata management, lineage, master data, and data quality disciplines.
• Experience building scalable data platforms from greenfield or lower-maturity environments.
• Ability to balance strategic architecture leadership with hands-on technical execution.
• Strong communication skills with the ability to influence executives, technical teams, and business stakeholders.

Preferred Qualifications

• Experience integrating ERP, financial, operational, construction, or project-control platforms.
• Exposure to Oracle Fusion, Oracle Unifier, Primavera, or similar enterprise platforms.
• Experience in energy, utilities, industrial operations, construction, critical infrastructure, or operational technology environments.
• Knowledge of industrial, telemetry, IoT, SCADA, or OT data architectures.
• Experience enabling AI and advanced analytics initiatives at enterprise scale.
• Background supporting digital transformation and enterprise modernization programs.
• Experience managing system integrators, consulting partners, and technology vendors.

Ideal Candidate Profile

You may currently be working as a:

• Enterprise Data Architect
• Principal Data Architect
• Chief Data Architect
• Director of Data Architecture
• Enterprise Architect (Data Focus)
• Head of Data Platforms
• Lead Data & AI Architect
• Data Platform Architect

You bring a combination of enterprise architecture leadership, modern data platform expertise, strong integration experience, and a passion for building the foundational capabilities that power analytics, AI, and future business growth.

Keywords

Enterprise Data Architecture, Data Platforms, Databricks, Snowflake, Microsoft Fabric, Azure Data Services, Data Governance, Data Engineering, Integration Architecture, Lakehouse, Data Warehouse, Data Lake, APIs, Event Driven Architecture, AI Architecture, GenAI, RAG, Vector Databases, Enterprise Architecture, Oracle Fusion, Unifier, Primavera, OT Data, Industrial Data, Energy, Utilities, Critical Infrastructure, Digital Transformation

Medical, dental, and vision insurance are available to qualified candidates who meet eligibility requirements.

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