Mohammed Taha EL AHMAR

Context: Data Lake House for Refinery and Chemistry data products. • Implemented data ingestion and transformation jobs triggered using predefined schedules. • Optimised end user data query performance using data modeling and delta table storage management best practices. • Reduced Databricks usage cost through compute tuning. • Developed code quality and data validation features. • Evolved CICD pipelines. Technologies: Pyspark, Python, Pytest, Databricks SQL Warehouse, Azure Databricks, Github actions, Azure Data Lake, Terraform, Liquibase, Databricks Genie.

Context: Maintenance planning web application for Oil & Gaz extraction platforms. • Implemented daily batch ETL workflows using Azure services. • Improved existing ETL code robustness and test quality with architectural best practices. • Developed CICD pipelines. • Evolved & deployed infrastructure services using Terraform IaC capabilities. • Delivered introductory trainings for Data Engineers on the following technologies: Databricks, Docker and Kubernetes Technologies: Python, Pytest, SQL, Azure functions & durable functions, Azur Service Bus, Gitflow, Github actions, Azure Data Lake, Azure SQL Database, Terraform, APIM

Co-animation de FORMATION des dirigeants des clubs Toastmasters @Paris 27 juin | Division A - Toastmasters International, District 59 France 🇨🇵

District Leadership Committee (DLC) 2023-2024

Context: Development and improvement of existing ETL workflows for operational and marketing data analysis. • Improved ad hoc notebooks on Spark Databricks to perform big data ETL pipelines. • Performed Data quality checks in collaboration with data analysts : SQL data querying in Azure SQ. Database in order to detect and fix inconsistencies in data flows. • Training of client data analyst to perform data transformations and troubleshooting in Databricks Technologies: Python, pySpark, Azure Databricks, Azure Blob Storage, Azure SQL Database

Context: Programming of a an ETL workflow for competitive pricing scenarios analysis and launch of new customer products • Developed and integrated new features to a pricing scenario evaluation model with graph analysis in python (agile mode) • Increased tests coverage • Deployed ETL workflows in Databricks Technologies: Python (pandas, numpy, networkit, networkx, pytest, koalas), Gitlab, Databricks, AWS S3

Context: HR payroll management, regulatory reporting of the employee inclusion indicators, gender equality label KPIs. • Developed ad-hoc and scheduled BI reports and KPIs using SAP BO, Power BI and SQL Developer. • Implemented data extraction AI use case from pdf documents using NLP & OCR python libraries. • Implemented a skills management POC with natural language processing technologies • Conducted forecast study on employee churn using Machine Learning models. • Developed an IA PoC for matching between employee profiles and internal mobility vacancies with natural language processing (NLP) techniques. Technologies: SQL Developer, SAP Business Object, MS Power BI, Cloudera, Anaconda, Python (NLTK, Spacy, Tkinter, Pandas, Numpy, Textract)