Enterprise Data Architect

We offer: Career Development Competitive Compensation and Benefits Pay Transparency Global Opportunities Learn More Here: Dematic provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. The base pay range for this role is estimated to be $134,250 to $205,850 at the time of posting. Final compensation will be determined by various factors such as work location, education, experience, knowledge, and skills. Tasks and Qualifications: What You'll Own: Technical vision including integration models and engineering standards. Architecture design, including schema/hierarchy, catalog strategy, technology, and API contracts. Implementation, including tech stack and toolset selection. Delivery strategy for a multi-year platform roadmap. Engineering quality, reliability, and secure-by-design practices from initial build through ongoing operations. What You Will Do in this Role: 1) Vision, Architecture, and Platform Strategy Define and maintain the technical vision, architecture principles, and engineering strategy for the Solution Data Repository. Lead the design and development of an enterprise ontology to inform the technical architecture. Establish robust design patterns, integration contracts, and data standards that enable lifecycle continuity from pre-sales to downstream execution and support. Own architecture decisions for core platform capabilities, including modeling/configuration, workflow orchestration, specification generation, and system interoperability. Define the technical approach for evolution, including where catalogs and project-specific configurations are authored, versioned, and persisted. Drive practical interoperability between catalog/SDF sources and downstream tools (for example simulation, emulation, software quoting, and delivery systems). Ensure platform design balances flexibility for customer-specific solutions with standardization for reuse, quality, and speed. Partner with product and domain leaders to align platform evolution with market needs, customer outcomes, and commercial priorities. Ensure platform design supports use of AI at enterprise scale, including context, semantics, and metadata. #J-18808-Ljbffr