Big Data Engineer

Integrated into a team of 9 people working in Agile (developers, product managers), I worked on designing new features and maintaining 4 strategic ETL chains processing judicial and financial data of European companies.

• Design and development of Natural Language Processing (NLP) features in Java and Scala
• Implementation of a pipeline validating daily XML files via JAXB using XSD schemas
• Deployment and maintenance of 4 batch ETL chains in REXX
• Creation of an Angular 20 UI for business data visualization
• Administration of Kafka topics and streams for data streaming
• Implementation of observability (SLO/monitoring) via Prometheus and Grafana dashboards
• Management of CI/CD pipelines (GLPI, Jenkins, SVN) including documentation, unit tests and code reviews

Big Data Engineer

Orange, French telecommunications leader, undertook the migration of its data to GCP Cloud. Within a team of 15 people, I accompanied this transition by optimizing ETL pipelines.

• Design and development of new features for ETL chains based on Kafka, Spark and ElasticSearch
• Development and implementation of a RAG (Retrieval-Augmented Generation) solution for an internal LLM (Dinootoo)
• Operational maintenance of Big Data applications (Kafka, Spark, NiFi, ElasticSearch, Airflow)
• Testing applications from on-premise to GCP environments (Cloud Composer, BigQuery, Big Table)
• Update and optimization of GCP DataFlow packages in Python
• Industrialization via CI/CD integration (GitLab CI, Jenkins, GCP)
• Participation in Agile (Scrum) rituals via JIRA/Confluence

Production Big Data Engineer

Within the FDJ Data Lake Production team, I was responsible for the reliability and availability of critical data, ensuring ETL pipeline maintenance, API development and monitoring dashboard creation.

• Operational maintenance of Big Data infrastructure (Apache Hadoop HDFS, Kafka, Spark, NiFi, ElasticSearch, Airflow, GitLab)
• Data Quality control via automated Python scripts
• Design, implementation and maintenance of ETL pipelines (creation and optimization of NiFi flowfiles)
• Development and deployment of APIs (FastAPI) for documentation data exposure
• Security certificates management (Kafka/ElasticSearch/NiFi)
• Continuous integration and deployment (GitLab CI, Kubernetes, Docker, Nexus)
• Agile Scrum rituals and technical documentation writing

Python Developer

Development of an OCR (Computer Vision) algorithm to extract and structure texts present in organizational chart images, automating document entry to save 90% of manual processing time.

• End-to-end Data Science project management
• Design of mathematical algorithms for identification and generation of bounding boxes covering essential texts
• Development, model accuracy evaluation and application testing
• Deployment of the packaged model on Microsoft Azure cloud

Full Stack Python Vue.js Developer

Integrated into the 'Deep Sector' project providing enriched financial data on TMT sectors. Within an Agile team of 20 people, my role was to improve data access for clients with high availability and low latency constraints.

• Design, development, documentation and maintenance of 3 critical APIs in Python/FastAPI
• Fullstack participation (component enrichment via Vue.js)
• Implementation of continuous integration via GitHub and deployment on AWS
• Writing unit tests (PyTest) and creation of Mocks via Swagger
• Daily collaboration with international project teams

Data Scientist

• Modeling of a complex physico-chemical process
• Creation, optimization and iterations of several machine learning, deep learning algorithms in Python: LSTM + GRU combined with a custom encoder layer of transformer architecture dedicated for time series forecasting
• Deployment of algorithms by Flask API
• Development environment: Linux + Azure (using GPU NC6)
• Exchange with experts
• Digital twin: developed machine learning-based models combined with physicochemical models to predict the end of the catalyst cycle