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.
We are looking for an Architect of solutions based on Data- Science who wants to develop his professional career in a growing company dedicated to solving complex problems in the business world through the development of advanced technologies. We offer you to work at the front line in 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 solutions, within the framework of the Data Science projects of the AIA Innovation unit. Your work will consist of:
- Understand the needs of customers and their technological environment, to propose the most appropriate technology and architecture for each case.
- Give support to Data Scientists in the definition of advanced technological architectures (Big Data, ML- Ops, Cloud, 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 developed.
- In coordination with AIA’s IT department, and when necessary, install and manage our own ML- Ops environments that imitate the client’s infrastructure, for development and testing.
In the AIA Innovation unit the projects are very varied, with very different technology stacks. Here is a brief list of some of the technologies we work with to industrialize our solutions:
- 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.
- Virtualization and containerization tools like Docker (mostly), Vagrant, VMware, and LXC containers.
- Task engines like Airflow or Celery.
- Cloud services under AWS and Azure.
- Distributed computing systems with PySpark in clusters such as Cloudera or DataBricks .
- ElasticSearch, InfluxDB ) databases.
- Code versioning with Git and Subversion.
These, however, are just an example–in each new project we are open to new technologies. You are expected to be able to decide (or at least discuss) in each project which architecture is the most appropriate for the case and guide our data scientists in that industrialization.
Minimum requirements
- Bachelor’s Degree in Computer Science
- Passion for understanding how IT works, from the foundations (the hardware, networks, and operating systems) to the top 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.
- Intermediate/advanced level knowledge of data management.
- Basic knowledge of a cloud environments: AWS, GCP, or Azure.
- Analysis and tuning capabilities, with a view to improving performance and scalability.
- Advanced English level.
Desirable experience/skills
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, Big Data, or ML- Ops.
