Freelancer profile translated to English.

Description

I am a Data Engineer Consultant, specializing in the design and industrialization of large-scale Data platforms. I work on the entire data processing chain: ingestion, transformation, modeling, orchestration, and data exposure, with strong expertise in Big Data and Cloud environments.

My experience covers both Build phases (design of Data architectures, pipeline development, historical data recovery, processing optimization, qualification, and testing) and Run and evolutionary maintenance activities, allowing me to adopt an approach focused on performance, reliability, and operational efficiency.

During my assignments, I have developed solid expertise around the Spark and Databricks ecosystems and distributed architectures, with an emphasis on data quality, scalability, and processing industrialization. Certified in Spark and Databricks, I have also contributed to upskilling teams through mentoring, technical coaching, and sharing Data Engineering best practices.

Recognized for my commitment, autonomy, and ability to propose solutions, I evolve effectively in demanding technical contexts focused on Data transformation.

Languages

Arabic
Native or bilingual
French
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Paris (up to 50km)

ENGIE
Data Platform
ENERGY AND UTILITIES
October 2025 - Today (10 months)
Paris, France
Within the Data Platform team, I joined to strengthen the team and contribute to achieving the One Platform BDP objectives. I was responsible for the build, run, and adoption activities of the data platform.
I contributed to the migration and industrialization of the platform (AWS, Databricks), the implementation of ingestion pipelines, CI/CD integration, as well as run and MCO activities (monitoring, support, cost optimization). I also participated in supporting business teams, defining best practices, and deploying data services, in a secure framework compliant with IT standards.
Databricks PySpark Gitlab CI/CD SQL Airflow
Enedis
DAD (Data Analytics for Distribution)
ENERGY AND UTILITIES
October 2024 - October 2025 (1 year)
Paris, France
Within the Smart Network Assets and Operations Product Line, I joined the DAD (Data Analytics for Distribution) team to develop data services and applications dedicated to the electrical grid. These developments include: targeting investments based on the incident-prone nature of power lines, preventive location of incidents on the medium voltage overhead grid by analyzing 'weak signals', modeling Low Voltage load, and flood monitoring.
The use cases, primarily developed in Spark and Scala, address the need to process large quantities of data. A significant part of the work involves data preparation, including cross-referencing multiple sources (electrical grid history, meteorological data, cartographic data, etc.), enriched by specific treatments such as graph analysis, geospatial calculations, and the application of machine learning techniques.
Spark Scala Python Airflow apache sedona
EDF
BI Foundation
ENERGY AND UTILITIES
February 2024 - October 2024 (8 months)
Paris, France
As part of the EDF mission, I worked on the BI Foundation project.

I contributed to setting up a CI/CD process to:
• Automate the deployment of Power BI reports from a git repository
• Automate the deployment of Informatica Processes and Taskflows from a git repository
• Automate the execution of SQL scripts on Snowflake from a git repository
• Automate and centralize nightly routines by developing a workflow that synchronizes tasks across the 3 platforms (Snowflake, Informatica, Power BI).
The project allows managing the sources of each platform using Git repositories with the Git Flow model.
Python Gitlab Informatica Snowflake Microsoft Power BI