Bilel Bouacha

Au sein de l'équipe data du programme ACTEE, je participe à la construction d'un inventaire national des bâtiments publics, destiné à mieux connaître le patrimoine des collectivités et à piloter sa rénovation énergétique : • Intégration et consolidation des déclarations transmises par les organismes publics dans une base unifiée afin de construire cet inventaire • Fiabilisation de l'inventaire par rapprochement avec les référentiels nationaux du bâtiment (RNB, BDNB, OpenStreetMap), avec un niveau de confiance attribué à chaque bâtiment pour orienter les vérifications • Développement d’un algorithme de fiabilisation et d’enrichissement de l’inventaire avec les déclarations de patrimoine des collectivités • Traitement des enjeux de qualité de données : doublons, adresses imprécises, distinction entre propriétaire du terrain et du bâtiment • Développement de traitements analytiques sur l'inventaire consolidé via manipulation de data géométriques/géographiques et spatial join avec Apache Sedona • Industrialisation des pipelines sur une plateforme cloud (Spark sur Kubernetes, Docker, stockage S3 OVH), Git, GitHub et PostgreSQL Compétences : Python, PySpark, Apache Sedona, données géospatiales, qualité de données, Kubernetes, PostgreSQL, Git

• Design, develop and maintain scalable ETL and data workflows on Databricks platform integrated with AWS for front office teams. • Collaborate closely with traders and market analysts to develop data applications to meet needs, unify data sources and establish a coherent data model. • Contribute to the automation of processes on the trading desk • Ensure the availability, integrity and performance of data pipelines. • Monitor workflows to maintain high data quality. • Analyze platform performances, identify bottlenecks, and recommend improvements. • Develop and maintain comprehensive technical documentation for ETL implementations and introduce the implementation of the new Databricks features.

Development and migration of use cases from Python and R to DataBricks: • Development and migration of use cases from Python/R to PySpark and DataBricks. • Optimization of PySpark workflows and code refactoring. • Monitoring and maintenance of the data platform. • Training of the team on Spark engine and DataBricks.

• Development of ingestion data pipelines with Luigi and PySpark to allow their consultation on PostgresSQL and MSTR for business teams • Development of a reconciliation engine to perform the reconciliation between accounting data and banking data • Development of accounting and banking data pipelines and creation of views in order to provide reporting for business teams • Development of SQL queries for querying financial data • Migration of workflows from on-premise platform to cloud Azure platform • CI/CD pipelines with GitLab/GitHub/Docker Kubernetes • Development of a test environment (for business tests with deployment of applications on Kubernetes cluster with Docker and ArgoCD) • Monitoring and maintenance of the data platform : fix KO workflows, debugging of existing workflows, investigation of root causes, analysis of logs with Loki, monitoring of application resources with Grafana, reporting of information and alerts via ServiceNow and JIRA tickets, definition of procedures to facilitate production monitoring

• Gather customer requirements • Managed data migration process : planning, specifications, configuration, risks • Data collection, analysis and storage with data warehousing concepts and ETL pipelines • Data preparation for KPI reporting/analytics and visualization tools, training of Key Users/End Users • Front-office support for Key Users/End Users in Hungary, Madrid and London

• Gather customer requirements to create scenarios (inventory, delivery time and logistics cost) • Data collection using Pandas • Reporting and dashboards of KPIs with Power BI for Data Analytics solutions • Implementation of an international flow from France to the Algerian plant (Oran), cost and volume optimization with RFQ