Dematic is building a next-generation Solutioning Suite to help our project teams implement end to end design, engineering, and management of customer-specific solutions with speed, quality, and confidence. We are seeking an enterprise data architect to define and implement the technical architecture for a Solution Data Repository, the foundational data platform for the Solutioning Suite. The Solution Data Repository will serve as digital thread or single source of truth for all solution-related data from lead qualification and solution design through implementation, commissioning, and long-term maintenance/support and enable the use of AI at enterprise scale.

This role requires both deep technical architecture experience and highly effective multi-functional communication and collaboration. The successful candidate is equally comfortable setting platform direction, making critical design decisions, aligning with stakeholders, and doing hand-on implementation work. This role presents a great opportunity to design and build an enterprise data solution from the ground up with much opportunity for career growth. It will appeal to someone with deep curiosity and someone who thrives on leading through ambiguity.

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.

2) Engineering Execution and Technical Governance

• Lead planning and execution of platform milestones, balancing near-term delivery with long-term scalability and maintainability.

• Implement and enforce engineering lifecycle standards, code quality practices, release discipline, and operational readiness criteria.

• Drive modern software engineering practices, including CI/CD, automated testing, observability, and risk-based release governance.

• Act as escalation point for complex technical challenges; unblock teams and lead issue resolution with urgency.

• Establish measurable engineering KPIs (for example reliability, throughput, quality, and adoption) and use them to guide decisions.

3) Cross-Functional Leadership and Customer Outcome Focus

• Partner with Product Management to translate strategic priorities into executable technical plans and roadmap trade-offs.

• Collaborate with functional partners to ensure tooling supports compelling, accurate, and scalable solution creation and evolution.

• Align with producing and consuming application teams on data contracts, adoption milestones, and readiness criteria for Solution Data Repository ingestion.

• Work in parallel with a tool suite architect who has knowledge of product design tools.

What We are Looking For:

Basic Qualifications

• Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).

• 5+ years of hands-on software architecture and development experience for data-centric integrated business platforms including an enterprise data architecture designed for integration, usability, scalability, and maintainability.

• Demonstrated ability to drive the design of scalable enterprise data ontologies, partnering with functional and application leaders, to ensure applicability of the design and subsequent adoption.

• Demonstrated success setting technical direction while delivering business outcomes in complex, cross-functional environments.

• Strong communication skills with ability to influence technical and non-technical stakeholders.

Preferred Qualifications

• Experience in supply chain, warehouse automation, industrial software, or enterprise solutioning domains.

• Experience building platforms that connect pre-sales configuration, solution design, and downstream delivery/operations workflows.

• Knowledge of model-driven or rules-driven solution design systems and specification generation workflows.

• Experience defining and governing shared data models/schemas and API-first integration for multi-team platforms.

• Experience integrating with PLM/catalog and configuration systems (for example Teamcenter) and simulation/emulation ecosystems.

• Experience with graph database technology and designing enterprise ontologies.

• Experience with cloud-native architecture, secure software development, and enterprise integration patterns.

• Experience defining engineering governance, quality frameworks, and platform standards at scale.