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About Me

·3 mins

I am a cloud engineer specializing in geospatial data infrastructure and DevOps automation. Currently at Development Seed, I design and build scalable cloud platforms for Earth observation data, enabling organizations like ESA, and ECMWF to process and analyze massive geospatial datasets efficiently.

I have hands-on experience with AWS services (ECS, Lambda, S3, VPC), Terraform and CDK for infrastructure management, Docker and Kubernetes for containerization, and comprehensive CI/CD automation. I’m passionate about open source, security best practices, and helping teams adopt cloud-native approaches for scientific data processing.

My Journey from Ocean Data to Earth Observation #

Before transitioning to cloud engineering, I spent 10 years as a research scientist 🧑‍🔬 developing data processing systems and computational workflows for oceanographic observations. This experience gave me strong foundations in systematic problem-solving, large-scale data pipeline design, and working with scientific data formats.

My technical journey started in scientific computing where I built data processing pipelines for large-scale oceanographic datasets collected from underwater buoys, research vessels, and satellite observations. I developed statistical methods to analyze time-series data and geospatial datasets, implemented quality control procedures for sensor networks, and created reproducible workflows.

This experience taught me the importance of robust data systems, systematic documentation, and reliable processing pipelines. All of these are essential skills for building cloud infrastructure that scientists and analysts depend on daily.

Academic Background & Research Experience #

I hold a Master of Science in Ocean and Atmosphere Physics from La Sorbonne University in Paris and a PhD in Physical Oceanography from Université de Perpignan Via Domitia (France)

I have always been interested in using technology to solve interesting data problems. After completing my PhD and a postdoctoral experience at CNRS and LOCEAN in Paris, I moved to Scotland where I worked at the Scottish Association for Marine Science in Oban as a research scientist for 4 years. Then I moved to England, working at the National Oceanography Centre in Southampton UK.

In my research, I developed and managed data processing workflows for ocean observation programmes, including underwater buoy arrays and underwater glider surveys. I also developed statistical methods to quantify ocean current strength and understand climate impacts. I built scientific libraries to process observational data from 🤖, 🚢 & 🛰️ and authored 30+ scientific articles 📄 published in peer-reviewed journals. I presented my work at 60+ international conferences 🗣️ (12 as invited speaker).

During those years, I spent 200+ days at sea 🌊 in the North Atlantic and Mediterranean 🌍, planning and co-leading fieldwork activities across 12 oceanographic research cruises.

Transition to Software Engineering & Cloud Infrastructure #

In 2021, I transitioned to software engineering, joining OSE Engineering as an R&D Software Engineer. I worked on Python libraries and full-stack development projects, taking responsibility for repository maintenance, code structure, documentation, and tutorials.

In November 2022, I joined the Department for Work and Pensions - Digital as a Software Engineer, developing cloud-based AI solutions for document processing and classification. In August 2023, I was promoted to Senior Cyber Platform Engineer, where I now focus on building secure, scalable platforms for AI workloads while mentoring junior engineers and improving team capabilities.

Now at Development Seed, I combine my scientific data processing background with modern cloud engineering practices to build infrastructure that enables Earth observation science at scale.

Loïc Houpert
Author
Loïc Houpert
I’m a cloud engineer at Development Seed focused on geospatial data infrastructure and Earth observation systems. I build cloud-native platforms and data pipelines that enable organizations to process massive satellite imagery datasets efficiently. With expertise in AWS, Terraform, Python, and Docker, I combine a decade of scientific data processing experience with modern cloud engineering practices.