Enterprise Architect (m/f/d)
On-siteDüsseldorf, North Rhine-Westphalia, Germany
Job Summary
Define and maintain architecture principles, standards, and reference architectures across domains like Consumer, Merchandising, and Supply Chain while owning technology roadmaps that align business strategy with technical direction. Establish governance through RFCs, ADRs, and design reviews, then assess major vendor decisions and steer build-vs-buy trade-offs. Maintain the enterprise architecture landscape to ensure decisions meet non-functional requirements for security, compliance, and scalability. Act as a bridge between stakeholders and engineering teams, translating strategy into actionable technical direction. Coach teams on architectural standards and review designs for conformance. Stay hands-on by validating decisions through building, prototyping, and directly contributing to platform and AI-assisted tooling. Design paved paths, templates, and self-service tooling to reduce toil for product teams. Take ownership of legacy systems and drive them to a stable, documented state. Build guardrails for AI-assisted development and improve CI/CD, provisioning, and internal documentation.
Required Qualifications
- 8+ years of hands-on software engineering experience
- Meaningful time in an architecture, platform, or technical-standards capacity
- Demonstrated ownership of architecture governance or standards for at least one significant domain
- Strong fundamentals in distributed systems, integration patterns, and cloud infrastructure
- Ability to remain hands-on: comfortable building, prototyping, or reviewing code and infrastructure
- Working experience with AI/ML-assisted development tooling
- Strong aptitude to build for AI/ML-assisted development tooling quickly
- Experience mentoring or informally leading engineers outside your immediate team
Desired Qualifications
- Formal enterprise architecture background or certification (e.g., TOGAF or equivalent framework experience)
- Experience with event-driven architectures (e.g., Kafka) at both the standards and implementation level
- Experience building internal developer platforms, self-service tooling, or golden path templates (e.g., Backstage or equivalent)
- Experience building or operating agentic AI development pipelines, evaluation frameworks, or AI-assisted CI/CD gates
- Exposure to data platform tooling (Fivetran, dbt, Snowflake or equivalent), SAP ecosystems, or retail/supply chain systems
- Familiarity with Domain-Driven Design as it applies to enterprise and service boundaries
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