Verified Expert in Engineering
DevOps Consultant and Developer
Daniel is a creative problem solver and critical thinker with an academic background in physics and over five years of industry experience in computing and solutions—from autonomous stratospheric gliders to data analysis platforms for satellites. Daniel enjoys working with problems from a conceptual stage up to completion and will often iterate over several prototypes in the process.
Ubuntu, Django, REST APIs, Docker, Docker Swarm, Python 3
The most amazing...
...thing I've built was a satellite data analysis platform for ESA: the Gaia Added Value Interface Platform (GAVIP).
Lead DevOps Consultant
- Helped design and implement many critical procedures within Enterprise, including the first implementation of a complete Ci/CD pipeline for critical infrastructure.
- Overhauled (eventually fully replacing) a legacy testing system with a complete unit and performance testing framework using Selenium and Locust. Tests could also be invoked using Jenkins pipelines which produced full reports with screenshots.
- Designed and built an extendible Python platform to better support ancillary tasks (such as reports) called Onyx. A full CI/CD pipeline was used to be rapidly tested and deployed. It's designed to replace tens of custom scripts.
Lead Architect | Full-stack Developer
- Designed a complete distributed and scalable platform to support a wide range of requirements.
- Liaised with multiple teams distributed across Europe, including gathering their technical requirements and providing documentation and workshops.
- Presented at several conferences, including SPIE, and hosted several in-person workshops and technical sessions.
- Ensured complete end-to-end traceability from various types of requirements to source code and unit tests. Traceability was described and provided in generated LaTeX documentation.
I took the platform from early sketches of workflows, through three iterations of architectural changes and optimizations, to a public tech demo hosted on AWS. The project encompasses technical documentation, front-end development, continuous integration, containerization, scaling, database query optimizations, and tech stack (Redis/PostgreSQL/Celery/Django) and capabilities optimization of available libraries in tandem.
I operated as the solution architect and lead developer (as well as wearing many other hats). I took GAVIP from early sketches on post-it notes to a complete platform deployed in the ESA data center in Madrid and delivered ahead of time ( around 15%).
The platform was required to support processing over 1PB of data and allow custom code to be contributed and shared among scientists with minimal manual intervention. I worked with multiple teams distributed across Europe to handle many different use-cases, from machine learning to interactive visualization of our galaxy.
So I designed, built, deployed, and got sign-off on a platform that allowed operators to add custom reports with credentials securely managed in Vault.
It helped save a lot of human hours each week and reduce the exposure to human error in critical reports.
Django, Selenium, Sphinx Documentation Generator, OAuth 2
REST APIs, Scikit-learn, TensorFlow, SciPy, Jenkins Pipeline, Keras
Docker Swarm, Chef, Pytest, Celery, Jenkins, LaTeX, Docker Compose, Vault
Docker, Ubuntu, Amazon Web Services (AWS)
Software Development, APIs, Machine Learning, HTTP, Distributed Systems, Thermodynamics, Photonics, Mechanics, Programming, Physics, Applied Physics, Front-end, Back-end, Scaling, Documentation, Redis Sentinel, WebSockets, Embedded Systems, CI/CD Pipelines, Python Performance, Software Design, Software QA
PostgreSQL, Redis, SQLite
Master's Degree in Physics (Specialization in Space Science and Technology)
University College Dublin - Dublin, Ireland
Bachelor's Degree in Physics
Waterford Institute of Technology - Waterford, Ireland
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