Camlin develops industrial technology and AI-driven systems used across the energy sector in more than 20 countries. We work on difficult real-world problems involving critical infrastructure, industrial sensor networks, and operational intelligence.We are looking for a Senior AI & Data Engineer to help design and deliver AI and data products focused on predictive maintenance, anomaly detection, asset monitoring, and energy forecasting. This is a hybrid working permanent role (3 days on-site, 2 days work from home).This is a highly hands‑on engineering role for someone who enjoys solving difficult AI and data problems in real operational environments. You’ll work closely with domain experts, product stakeholders, and engineers to turn data into reliable systems that create measurable business impact.We are looking for someone who can combine strong technical execution with the ability to bring structure, clarity, and momentum to complex engineering initiatives.



You’ll play an important role in shaping technical plans and driving delivery across AI and data projects.What you'll work on:Predictive maintenance systems for critical infrastructureAnomaly detection on sensor dataAsset monitoring and operational intelligence platformsEnergy forecasting and time‑series modelling systemsWhat you'll do:Design and build AI and data systems from early concept through model creationWork closely with data scientists, product managers, and domain experts to shape technical solutionsTurn ambiguous business and operational problems into structured engineering plansPrototype and validate ideas quickly to reduce technical and product risk earlyBuild scalable data and ML workflows using modern cloud‑native toolingInfluence technical direction, architecture decisions, and product roadmap discussionsEvaluate trade‑offs between model accuracy, reliability, complexity, latency, and operational costHelp drive measurable outcomes with clear KPIs and visible business impactImprove engineering

📌 Senior Data Engineer (Madrid)
🏢 Camlin Group
📍 Madrid