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Darwin Recruitment are hiring for a Senior Data Engineer for a business in Luxembourg that are a climate-tech / geospatial-data company that builds and operates satellites to gather thermal infrared and multispectral imagery of Earth. They launched its first satellite, in 2024 on a SpaceX Transporter mission, this was the first commercial satellite to deliver high-resolution thermal imagery with global coverage. They followed up with a second satellite, launched in 2025 (on Transporter-14). It carries advanced multispectral + thermal IR sensors and greatly increases the volume & speed of data collection. Farmers and agribusinesses use this company to optimize irrigation, reduce water waste, and increase crop yields. For many users, thermal imagery gives early warnings of water stress before visible signs appear. Their mission is to capture and deliver high spatio-temporal resolution thermal infrared data, currently not available from other sources, to provide insights that benefit the environment, enhance food and water security, and serve other critical applications. Their downstream applications team in Luxembourg combines best-in-class remote sensing, machine learning, and cutting-edge fusion approaches to thermal imagery to deliver innovative and scalable solutions to the agri-food industry. As a Senior Data Engineer you will design and implement state-of-the-art data pipelines using a modern cloud-native tech stack. You will optimize cloud infrastructure and scale data solutions to support real-time analytics and business growth. Beyond hands-on development, you will mentor other data engineers, conduct code reviews and contribute to defining best practices. Your work will include cross-functional collaboration with software engineering and science.
Job Responsibility:
Design and implement cloud-native data pipelines
Optimize performance and scalability of existing data pipelines
Deploy and maintain cloud infrastructure (AWS)
Take ownership of system components from concept to delivery
Mentor team members
Collaborate with Data Scientists to bring scientific models to production
Requirements:
5+ years of combined experience in Data Engineering, Cloud Engineering or similar roles
Proficiency in designing scalable, efficient, and maintainable data pipelines and architecture
Proficiency in deploying workloads on Kubernetes clusters
Strong experience with Apache Airflow
Experience in building and managing ETL workflows for data extraction, transformation, and loading
Experience with software development life cycle: design, development, test, deployment, operations
Proficiency in Python and Python data stack
Working knowledge of some infrastructure-as-code framework, preferably Terraform
Highly self-motivated, keen learner able to solve challenging problems with creative solutions
Strong team player with demonstrated ability to take ownership and drive execution
Nice to have:
Expertise with AWS cloud provider
Understanding of MLOps best practices for monitoring, versioning, and maintaining models in production
Experience in Earth observation, AI, geospatial, imaging science, or computer vision fields
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