Grupo AIA develops advanced software based on optimization techniques, simulation, and Machine Learning (classification, prediction, etc.), both on Big Data and on standard databases. For this, it applies methodologies based on basic sciences, fundamentally Mathematics and Physics. The permanent objective of Grupo AIA is the transformation of information into useful knowledge, which provides our clients with rigorous decision-making support, based on data, at all operational and management levels of their company.
At Grupo AIA we are looking for a Junior Cloud Engineer for solutions based on Data Science who wants to develop his professional career in a unique company, dedicated to solving complex problems. We offer you to work on the first line of truly cutting-edge innovation projects, for some of the largest companies in the country. You can see some of our past projects on our website, http://aia.es .
What is expected of you and what will your deliverables be?
You will work as an architect and developer in the industrialization of Cloud solutions, within the framework of the Data Science projects of AIA’s Innovation unit. Your work will consist of:
- Understand the needs of customers and their Cloud environment, to propose the most appropriate technology and architecture for each case.
- Provide support to Data Scientists in the definition of advanced technological architectures (Big Data, ML- Ops, etc.) that take into account the client’s production environment and ensure good performance, scalability, and easy inspection for maintenance and diagnosis of bugs and failures.
- Support the Data Scientists team in terms of industrialization, performance optimization, scalability estimates, etc., of the code they develop.
- Port and/or develop new code that implements the solution devised by the Data Scientists.
- In coordination with AIA’s IT department, when necessary, manage our own Cloud environments that imitate the client’s infrastructure, for development and testing.
Cloud environments could be any (AWS, Azure, GCP…) since our clients are very varied and have very different technology stacks. Software technologies are also very varied:
- Web development with Django, FastAPI, Streamlit, Dash, or R Shiny, as well as frontend frameworks like VueJS and Vuetify.
- Dashboarding applications such as Grafana, Kibana, Tableau, or PowerBI.
- Deployment and maintenance through virtualization and/or containers: Docker (mainly), LXC/LXD, Vagrant, VMware, etc.
- Task engines like Airflow or Celery.
- Distributed computing systems with PySpark in clusters such as Cloudera or DataBricks.
- ElasticSearch, InfluxDB) databases .
All this is for informational purposes, to show that in each project we usually tackle different technologies. You are not expected to know about all of them–far from it. What is expected of you is that you enjoy to always be learning new stuff to be up-to-date, and in this way be a person who can lead decisions regarding architecture and infrastructure in our projects.
- Bachelor’s degree in computer science
- 1 year experience and medium-level knowledge in a Cloud environment : AWS, GCP or Azure.
- Passion for understanding how IT works, from the foundation (hardware, networks, operating systems) to the bottom of the stack (what the final application code does).
- Solid knowledge of programming and IT systems. It is especially important to master Python, which is the language we use the most now.
- Intermediate level knowledge of TCP/IP and networks.
- Intermediate level knowledge in data management.
- Analysis and tuning capabilities, with a view to improving performance and scalability.
- Advanced English level.
The items on the following list are not essential, but they will give you an idea of what we will value additionally:
- Experience as a Developer / Analyst / Architect in production environments.
- Knowledge of IT systems in general (hardware, OS, virtualization, networks, etc.)
- Knowledge in Clustering and Distributed Computing.
- Personal projects on Github and/or other open- source contributions.
- Experience managing communications with clients: presentations, work sessions, follow-ups.
- Experience in supporting the implementation of solutions in customer environments.
- Master in IT Systems, ML- Ops, or Data Engineering .