Description

Enthusiastic Engineer, passionate about Big Data and its endless possibilities. Looking for new challenges, I’m self-motivated, curious and open-minded. I believe In giving my best be it work or at improving myself whether by learning new things, practicing languages or developing my professional skills. My strengths are my adaptability, an extensive hunger for learning as well as my ability to find innovative solutions.

Langues

Français
Bilingue ou natif
Anglais
Bilingue ou natif

Préférences en matière de lieu de travail

En télétravail uniquement

Travaille majoritairement à distance

Relive
Data Engineer
RÉSEAUX SOCIAUX
mars 2022 - Aujourd'hui (4 ans et 3 mois)
• Built large scale data pipeline to process geospatial user data to feed the "Route Navigation" feature on the Relive mobile app using Apache Spark and various geospatial processing libraries (H3, Apache Sedona)
• Contributed to major migration to new event tracking system (Snowplow)
• Improve and maintain the AWS Redshift data warehouse using Data Build Tool (dbt) for the transformation and modeling layer
• Work closely with data analysts, assisting them with their data needs and writing complex queries
DBT Spark Amazon Redshift AWS Python Scala Terraform
Société Générale
Data Engineer
BANQUE & ASSURANCES
mai 2021 - janvier 2022 (8 mois)
Paris, France
• Designed and built a data versioning framework with Spark for data stored in Hive
• Tuning and optimising running environment on Spark reducing the ingestion phase of raw data from 2 hours to less than 8 minutes
• Working closely with Data Analysts in the design of ETL processes
Spark Hadoop Scala ETL Hive Big Data Oozie Jira SQL Git Data Modelling
banque de France
Data Engineer
BANQUE & ASSURANCES
février 2019 - avril 2021 (2 ans et 3 mois)
Paris, France
• Designed with a Data Architect and built from the ground up the data management and processing system in a DataLake On-premise for performance at scale
• Worked closely with stakeholders from different departments to ensure architecture met business requirements and to identify ways to improve data system functionalities and flexibility
• Designed Data Warehouse model and complex queries (HQL/SQL)
• Data pipeline optimisation, continuous monitoring and regular testin
Spark Hadoop Hive Scala Java Oozie Jira Elasticsearch Bash SQL Git XLDeploy Jenkins