Bady Ben Salah

I joined the Orion Project Core Team to build Chanel’s new enterprise Data Platform on Microsoft Fabric. Following the global rollout of the new POS system, my team was responsible for ingesting its data end‑to‑end and migrating more than 30 legacy system sources from the Azure ADF/Databricks environment into Microsoft Fabric across all Chanel entities. The main technical responsibilities include: - Developement of Fabric Notebooks/Pipelines/ EventSteams... - Developement of CI/CD Azure DevOps pipelines. - Migration of legacy code from Azure Data Factory/ Azure Databricks/ Azure Functions into Fabric. - Technical environment : Pyspark, Sql, Power Shell, Fabric, Azure Data platform (ADF, Databricks, Synapse, ADLS Gen2...) Git, Azure DevOps

Within Construction Chemicals BUs, I designed and delivered a global end‑to‑end data platform capable of ingesting and harmonizing data from all CC legal entities worldwide. More than 25 heterogeneous sources — including SAP, Sage X3, Snowflake, SharePoint drops, MDM systems, and various REST APIs — were integrated through standardized ingestion pipelines. Data was cleaned, transformed, consolidated and modeled to produce Analytics‑Ready Data Marts, supporting both operational and strategic use cases. The platform also feeds Magnitude with critical commercial and master data (Sales, Products, Customers, etc.), ensuring a single source of truth and enabling reliable reporting, forecasting and performance steering. Main developments include : - Synapse/ADF pipeline developments. - SQL (Stored Procedures) and PySpark developments. - Functional requirements gathering. - Project architecture improvments

Within the RISQ/CTL division, I led the industrialization of the bank’s regulatory and operational‑risk reporting data pipelines. I transformed raw data‑lake dumps into high‑quality, governed data assets, enabling consistent, auditable and high‑performance reporting across the group. I designed and optimized Azure Synapse and Data Factory pipelines, built SSAS/AAS cubes and Analytics‑Ready Data Marts, and delivered Power BI applications used daily by regulatory, compliance and operational‑risk teams. This work significantly reduced data preparation time, improved reporting reliability, and accelerated regulatory submission cycles. I also drove performance optimization across the entire analytical chain, improving cube refresh times, stabilizing ingestion workflows, and increasing the scalability of the platform for future regulatory requirements. Technical Environment: ADF, Azure Data Lake Gen2, Synapse, PySpark, SQL, Azure DevOps, Power BI Premium, GitHub, SAFe.

Within the global Procurement BI organization, I led the consolidation and industrialization of Thales’ worldwide procurement data. I integrated and harmonized data coming from all ERP systems across all Thales entities and subsidiaries — including SAP, SAP ByDesign, Oracle, XML dumps, Parquet exports, and other heterogeneous sources — into a unified analytics‑ready data platform. I migrated legacy Python‑based ETLs and delivered robust Azure Synapse / Data Factory pipelines, enabling reliable ingestion, transformation and standardization of procurement data at scale. I designed and developed Data Marts, Data Warehouses, and AAS cubes, powering high‑performance analytics for global procurement stakeholders. I also built Power BI reports, dashboards and applications consolidating worldwide Spend, Cash, supplier performance and multiple strategic procurement KPIs. These assets significantly improved data reliability, accelerated reporting cycles, and enabled unified cross‑entity visibility for decision‑makers. Technical Environment & Methodology: SQL, ADF, Synapse, PySpark, AAS, Power BI, DAX, Azure DevOps, Git, SCRUM, JIRA.

Within the RISQ division, I led the modernization of the bank’s regulatory and operational‑risk analytics platform by expanding and industrializing Azure‑based data services while maintaining critical on‑premise SSAS/Report Server assets. I worked closely with business teams to identify regulatory needs, translate them into functional specifications, and design multidimensional data models supporting high‑volume, audit‑ready reporting. I delivered Spark‑SQL ETL pipelines and built Azure Data Factory, Azure Synapse, Azure SQL Database, and Azure Data Lake Gen2 components to migrate and modernize ingestion, transformation and analytical workflows. On the analytical layer, I developed AAS/SSAS OLAP cubes and Power BI dashboards, enabling unified, reliable and faster reporting across risk, finance and compliance. This Azure‑driven modernization reduced manual data preparation, improved reporting reliability, and accelerated regulatory submission cycles, while the hybrid architecture ensured continuity of legacy reporting during the transition. Technical Environment & Methodology: Azure Data Factory, Azure Analysis Services, Azure Synapse, Azure SQL Database, Azure Data Lake Gen2, SSAS, HDFS, Spark‑SQL, Hive, MDX, DAX, Power BI, Azure DevOps, Jenkins, GitHub, SCRUM.