About Nicolas
- Cloud-native architecture (Azure, GCP, AWS)
- Real-time streaming and large-scale data processing
- ML system design and production deployment
- Prototyping AI agents and MCP-based solutions in enterprise environments
English
Fluent
Japanese
Basic
French
Native or bilingual
Experience
- Société GénéraleAzure Data Solutions Architect Java/PythonBANKING AND INSURANCEApril 2022 - June 2023 (1 year and 2 months)Puteaux, France🏗️ Within the "Datahub" teams of a major French bank, implemented a Data platform enabling migration and technical/functional evolutions towards Azure Cloud.• Migration from Apache Spark 2.4.8 -> 3.1.1• Development of financial data products with Apache Spark• Development and production support of data products operated by Java API• Team coaching and upskilling on the Data aspect• Implementation of Data job orchestration with Airflow on on-premise managed Airflow• Management of both on-premise and Azure cloud infrastructures/services• Contribution to architectural choices and maintenance of architectural standards• Contribution to the delivery of 3 feature teams using a DevOps approach🛠️ Technical Environment: Java, Python 3.9, AKS (Azure Kubernetes Service), Azure HDInsight (Managed Spark Cluster), Azure Storage ADLS Gen2, Azure PostgreSQL, Azure Key Vault, Kubernetes and on-premises service management, Airflow, Docker, Spark on AKS, Spring Boot, Python Poetry, Terraform, Jenkins, Sonar, Conventional Commits, Apache Kafka, Hive, Zeppelin, Delta Lake
- KadensisMachine Learning Engineer Python JavaAUTOMOBILEMay 2020 - May 2022 (2 years)Full Remote🏗️ Implemented an architecture using Machine Learning to consolidate articles from various automotive catalog sources on AWS.• Migration from Spark 2.4.5 -> 3.1.1• Development and production support of data products operated by Java API (on Mongodb/Elastic)• Industrialization of Pyspark jobs with ephemeral clusters on AWS EMR• Implementation and production deployment of Machine Learning data products• Interpretation and improvement of article/catalog matching model results• Team coaching and upskilling on Data (PySpark) / Machine Learning• Implementation of Data Quality on incoming data with Great Expectations• Implementation of Data and ML job orchestration with Airflow🛠️ Technical Environment: Python 3.7.9, Spark, PySpark, AWS Elastic Map Reduce (EMR), AWS Athena, scikit-learn, MLFlow, Gradient Boosting, LightGBM, Deep Learning Keras, MongoDB, Java 8, Spring Boot2, Maven 3, Jenkins, AWS ELB, AWS Lambda, Elasticsearch, Great Expectations, Airflow
- Matcha.coMachine Learning Engineer PythonE-COMMERCEFebruary 2022 - February 2022Full Remote🏗️ Implemented GCP Cloud infrastructure, CI/CD for Python anonymization jobs, and an AutoML lead scoring MVP.🛠️ Technical Environment: Python 3.10, Pandas, Airflow (Cloud Composer), GCP, DBT, BigQuery, Gradient Boosting XGBoost, LightGBM, AutoML, Terraform, Gitlab CI, Airbyte, Docker
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Education
- Bachelor of Science and Technology in Computer ScienceUniversité Pierre et Marie Curie2007
- Expert in Software and System Development Management and EngineeringAFTI ETGL2010
Certifications
- Hugging Face Agents Course - Certificate of CompletionHugging Face2025
- AI Agents FundamentalsHugging Face2025