Enterprise Data Architect (Data Platforms, Integra (1150826)

About the role

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.

Location: Dallas, TX

Responsibilities

• 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, Retrie