About this role
Role Objective: Build, scale, and maintain the core data platform, backend applications, and REST APIs for real-time passenger timeslot services and operational capacity balancing. Act as a bridge between product owners, data scientists, and engineering teams to deliver reliable, production-grade solutions. Backend & API Engineering: Develop and maintain robust Python backend services and REST APIs for internal and external consumption. Data Pipelines & Integrations: Construct reliable data pipelines and integrations to support real-time operational workflows and capacity products. Cloud & Operations: Deploy, manage, and monitor applications in Azure and Kubernetes/OpenShift production environments. Reliability & Incident Management: Drive high availability, platform resilience, continuous improvements, and rapid troubleshooting/incident response. Data Science Productionization: Operationalize and scale machine learning models and data science products into production. Engineering Standards: Enforce CI/CD pipelines, automated testing, clean code practices, and modern software engineering standards. Mandatory Technical Experience: Backend & APIs: Strong professional experience with Python backend engineering and REST API design. Cloud & Containers: Hands-on deployment and management in Microsoft Azure (including Azure Database for PostgreSQL) and Kubernetes/OpenShift. Databases & SQL: Advanced proficiency in PostgreSQL and complex SQL querying. DevOps & Delivery: Production monitoring, troubleshooting, CI/CD pipeline setup, and Git workflows. Integration: Proven record of delivering data-intensive platforms and external-facing APIs. Languages: Professional fluency in English (team operations) and Dutch (stakeholder collaboration). Preferred Skills: Big Data: Experience with Databricks. Asynchronous Processing: Familiarity with Celery, RabbitMQ, or Redis. System Resilience: Background supporting high-availability or mission-critical enterprise environments.