Hydrosat is a space and data analytics company building a new Earth Observation constellation and software to unlock the power of thermal infrared imagery. Our 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. Our 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.

We are looking for bright, creative, and ambitious people who can work in a dynamic and collaborative start-up environment. Hydrosat is determined to change the way people use space imagery and revolutionize agriculture. Join us on this mission and help transform the world.

What you’ll do

As a Cloud Data Engineer you will provision and maintain infrastructure for highly scalable (petabytes) data processing using a modern data engineering stack including Kubernetes Terraform and AWS. You will create multi-environment CI/CD pipelines for testing and deploying code as well as implement data processing and machine learning pipelines at scale. Your work will include cross-functional collaboration with software engineering and science.

Responsibilities:

• Deploy and manage cloud infrastructure (AWS)
• Optimize performance and scalability of existing data pipelines
• Design, deploy and maintain new data pipelines in the cloud
• Lead technical and architectural discussions
• Take ownership of system components from concept to delivery
• Mentor team members

Requirements

• 5+ years of combined experience in Data Engineering, Cloud Engineering or DevOps roles
• Experience with setting up and maintaining cloud infrastructure
• Experience with implementing and maintaining data pipelines
• Experience with provisioning and maintaining Kubernetes clusters
• Experience with software development life cycle: design, development, test, deployment, operations
• Experience building and operating CI/CD pipelines
• 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

Desired Qualifications

• 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

Benefits

• Attractive compensation package
• Equity through stock option plan – be part of our long-term success
• Fast-paced, dynamic startup environment with real impact and ownership
• Hybrid work model – 1 remote day per week
• Work-from-anywhere flexibility – up to 2 weeks per year