Ylies C.

• Develop and maintain the platform to ensure an optimal user experience and meet evolving operational needs

• Collaborate closely with business and operational teams to gather requirements and design robust, scalable solutions

• Work jointly with UX/UI teams to implement intuitive and effective frontend features, integrating their feedback into the development process

• Ensure complete code coverage and rigorous testing strategies, including unit and end-to-end tests, to guarantee software reliability

• Work alongside the dedicated DevOps engineer to resolve issues and optimize the Microsoft Azure infrastructure, running on Docker and Kubernetes

• Participate in team collaborative practices such as group code reviews (mob reviews), pair programming, and design discussions to promote code quality and knowledge sharing

• Design and development of fully serverless data pipelines (AWS)

• Participation in the development of the API used by the new MyArkema customer portal

• Migration of the entire codebase to the latest version of Node.js

• Close collaboration with our clients (from design to acceptance testing in a Quality environment).

• Participation in team meetings (daily scrum, sprint planning, sprint review, etc.)

- Design, development, and maintenance of the data lake to provide internal data to decision-makers and marketing teams

- Implementation of an ETL pipeline in NodeJS, leveraging AWS and ElasticSearch, to aggregate, enrich, and ingest millions of daily usage data hits into our data lake for analytical purposes, for sending to external providers (Piano formerly AT Internet, Médiamétrie), and for use in our recommendation systems

- Implementation of Argo workflows to re-ingest historical data into the data lake in the rare cases of pipeline failure, to ensure data integrity

- Migration from RabbitMQ to Kafka in our data enrichment pipeline to switch to real-time processing and interface more coherently with the rest of our internal services

- Collaboration with various technical teams within the Digital Department to understand and meet their needs, as well as to support them in using and adopting the tools provided by our team

- Implementation and industrialization of machine learning algorithms for our personalized recommendation systems using MLflow (development of microservices in Python, management of their integration with our frontends, implementation of automatic model retraining processes on the cluster via k8s cronjobs)

- Development, maintenance, and evolution of search engines used on our websites and applications

- Collaboration with product and infrastructure teams to design optimal technical solutions