Summary
✨ AI‑Generated
A data engineering role within a digital engineering team building reliable, real-time services for complex operational workflows. You will develop and scale backend applications, REST APIs, and data-intensive services, while collaborating with product, data, and engineering specialists to turn complex operational requirements into robust technical solutions.
Highlights
32-hour work week with a hybrid or fully remote option subject to one mandatory weekly office day, working on real-time data platforms and operationally important backend services.
Description
About the job Data Engineer – Passenger Flow & Platform Services 260901-JAS-001Data Engineer – Passenger Flow & Platform Services 260901-JAS-001
Role Overview
Role Title: Data Engineer
Work Shift / Hours: 32 Hours / Week
Location: Hybrid / Fully Remote Option (1 mandatory on-site office day per week on Tuesdays)
Educational Requirement: Higher Professional Education (HBO level or equivalent)
Position Summary
We are seeking a Data Engineer to join a dedicated digital engineering team focused on creating seamless, highly predictable passenger flows and operational capacity balancing.
In this role, you will be responsible for the core data and software platform powering real-time passenger timeslot services.
You will build, maintain, and scale backend applications, REST APIs, and data-intensive services that support critical operational decision-making.
Working closely with product owners, data scientists, and cross-functional engineering teams, you will translate complex operational needs into production-grade, highly reliable digital solutions.
Key Responsibilities
Backend & API Engineering: Design, develop, and maintain robust Python backend services and REST APIs for internal and external consumption.Integrations & Pipelines: Build reliable data integrations and pipelines supporting core capacity balancing products and real-time operational processes.Cloud & Container Operations: Deploy, monitor, and operate applications in production environments utilizing Azure and Kubernetes/OpenShift infrastructure.Platform Reliability & Support: Ensure high availability and system resilience through active monitoring, troubleshooting, incident resolution, and continuous technical improvements.Data Science Productionization: Collaborate directly with data scientists to operationalize and scale machine learning models and data products into production.Engineering Best Practices: Champion software engineering standards, CI/CD automated pipelines, comprehensive testing, and clean code principles.
Candidate Qualifications & Competencies
Mandatory Technical Experience
Backend Development: Strong professional experience in Python backend development and REST API architecture.Containerization & Cloud: Direct experience deploying and operating production applications using OpenShift and/or Kubernetes, alongside Microsoft Azure (including Azure Database for PostgreSQL).Database Management: Advanced proficiency in PostgreSQL and complex SQL queries.DevOps & Delivery: Proven track record in production monitoring, incident resolution, CI/CD pipeline configuration, and Git-based development workflows.System Integration: Hands-on experience delivering data-intensive platforms and APIs consumed by external services.Languages: Professional working proficiency in English (primary team delivery language) and Dutch (required for effective stakeholder collaboration).
Preferred Skills (Nice-to-Have)
Experience with Databricks for big data processing.Familiarity with asynchronous task processing technologies such as Celery, RabbitMQ, or Redis.Background in developing and maintaining high-availability or operationally critical enterprise systems.
