At Xoople, we're building the Earth's data infrastructure layer for AI. Our mission is to enable AI to understand and predict physical changes on the world's surface by creating Earth's System of RecordTM—a trusted, enterprise-grade data foundation that connects the physical world to digital systems. By transforming vast amounts of Earth observation data into actionable insights, we help enterprises and governments make faster, smarter decisions about risk, operations, sustainability, and growth.

As a Senior Enterprise Product Engineer, you will design and deliver scalable Data & AI products that transform Xoople's Earth data into enterprise-grade, analytics-ready solutions. You will combine large-scale data processing, machine learning, and modern data architectures to enable advanced analytics and decision-making for customers and internal teams. Success in this role means taking solutions from concept to production, scaling AI workloads, and enabling seamless integration of Earth data into enterprise environments.

Design and deliver scalable, high-performance Data & AI products and pipelines. Develop machine learning and statistical models on large-scale datasets to enable advanced analytics. Design modern data architectures that make data reliable, accessible, and analytics-ready.

Build and operate end-to-end data pipelines and AI workloads in cloud environments. Collaborate with product, engineering, and commercial teams to translate enterprise needs into scalable, production-ready solutions. Improve platform scalability, reliability, and efficiency through cloud-native and distributed computing practices.





Strong, demonstrable experience designing and delivering cloud-native Data & AI products across the full product lifecycle. Hands-on experience with large-scale data processing and machine learning in production environments. Strong expertise in distributed computing frameworks such as Apache Spark or similar technologies.

Solid understanding of machine learning workflows, including model development, deployment, and inference. Strong knowledge of modern data architectures, including data lakes, lakehouses, and transactional layers.

Experience with cloud and data platforms such as Azure and Databricks.

Strong

Python programming skills and experience applying CI/CD practices to data and ML pipelines. Strong analytical and problem-solving skills, with the ability to collaborate effectively across engineering, product, and business teams. Degree in Computer Science, Data Science, Engineering or a related field, or equivalent practical experience.

Experience with geospatial, satellite, or imagery data.

Experience with MLOps and model monitoring tools such as MLflow.

Experience with orchestration and data quality tools such as Airflow and Great Expectations. Industry experience in financial services or another data-intensive sector.

We offer a competitive compensation and benefits package designed to support your wellbeing and growth, together with meaningful ownership, continuous learning and the opportunity to build a world-first Earth data capability with a integral, mission-driven team. We live it through four guiding principles:

📌 Senior Design Engineer (Madrid)
🏢 Xoople
📍 Madrid