обновлено 8 дней назад
Lead Integration Architect (Kubernetes/IoT)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead Integration Architect (Kubernetes/IoT): Defining and implementing integration architecture standards for a unified software ecosystem connecting instruments, applications, platform services, and enterprise systems with an accent on API design, event-driven architecture, schema governance, and versioning. Focus on architecting Kubernetes-based integration solutions, securing machine-to-cloud data exchange, and solving complex cross-system integration challenges across connected devices and software platforms.
Location: Barcelona, Spain
Company
connects scientific instruments, applications, and platform services into a unified software ecosystem.
What you will do
- Design and own integration architecture across software platforms, instruments, applications, and enterprise systems.
- Define and validate standards for REST and GraphQL APIs, event-driven architecture, asynchronous messaging, schemas, and versioning.
- Architect and provide hands-on guidance for containerized integration solutions running on Kubernetes across edge and cloud environments.
- Review critical integration designs, make binding architecture decisions, and drive adoption of scalable integration patterns.
- Build reusable integration patterns, reference implementations, working code, and architectural blueprints.
- Lead integrations involving connected instruments, laboratory systems, IoT devices, edge computing, and machine-to-cloud data exchange.
Requirements
- 10+ years of software engineering or architecture experience, including 5+ years in hands-on integration architecture.
- Deep expertise in REST/GraphQL API design, event-driven architecture, Kafka, MQTT or equivalent technologies, asynchronous messaging, schema governance, and API versioning.
- Strong hands-on experience with Kubernetes, Docker, and cloud-native deployment patterns.
- Experience integrating connected devices, instruments, industrial equipment, IoT platforms, or similar hardware-centric ecosystems.
- Strong understanding of device connectivity, telemetry, edge computing, machine-to-cloud communication, and real-time data integration.
- Ability to own implementation quality and make binding architecture decisions across teams.
Nice to have
- Experience in scientific instrumentation, laboratory software, or regulated industries such as life sciences and diagnostics.
- Familiarity with service mesh, API gateways, GitOps, infrastructure-as-code, and DevSecOps.
- Experience integrating AI/ML inference services and data pipelines.
- Background integrating systems across organizational boundaries or external partners.
Culture & Benefits
- Full-time weekly schedule with a day shift.
- 25% travel required.
- Permanent position with no stated end date.
- Compensation is determined by role, level, work location, skills, experience, and education or training.
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