Freelancer profile translated to English.

Description

Passionate about technology and data, I have focused my career around Business Intelligence and technological development.

As a Data Engineer, I have in-depth expertise in database administration, Big Data Analytics, and Business Intelligence, honed within leading organizations. At Ooredoo, I implement advanced data management technologies and data strategies to optimize operational efficiency. Previously, at Cosider Ouvrages d’Art, I made a decisive contribution to the deployment of data solutions for civil engineering projects.

Graduated with a degree in Computer Engineering and a Master's in Big Data Analytics from Badji Mokhtar Annaba University, and pursuing an MSc in Data Science at INSEEC Paris, my goal is to place data at the heart of business strategy. My approach combines continuous learning and Big Data analysis to design innovative solutions, thereby boosting organizational performance.

Industry field of expertise

Languages

French
Native or bilingual
English
Fluent
German
Conversational

Workplace preferences

Can work on-site

Paris (up to 50km)

Groupe SII
Data Engineer / Data Scientist
ENERGY AND UTILITIES
September 2025 - February 2026 (5 months)
Lyon, France
I participated in a research and development project on decentralized energy communities, aiming to improve collective self-consumption and support the energy transition. My role consisted of developing photovoltaic production and consumption forecasting solutions, based on real data, to better anticipate energy flows and optimize their use.

I contributed to an R&D project on decentralized energy communities, developing forecasting and energy optimization solutions based on real data. My role involved data validation, automating processing pipelines, preparing datasets for forecasting, and integrating results into a prototype with the technical teams.

• Contribution to an R&D project for energy forecasting and optimization on an AWS Cloud Data Platform, in a Modern Data Stack / Big Data environment.

• Design of ETL/ELT pipelines to collect, clean, transform, and historicize energy data (PV production, consumption, weather).

• Structuring data flows in a Data Lakehouse / Data Warehouse architecture with Medallion logic (Bronze / Silver / Gold) to ensure data reliability and facilitate its exploitation.
• Development of data processing with Spark and SQL to prepare datasets for forecasting, analysis, and prototyping.

• Implementation of quality controls, workflow automation with Airflow, and dataset preparation for forecasting and analysis.

• Integration of results into a prototype, with BI visualization and deployment in a containerized environment (Docker / Kubernetes).
Python Spark SQL ETL/ELT Amazon Web Services
OOREEDO - TELECOM,
Data Engineer
TELECOMMUNICATIONS
September 2024 - March 2025 (6 months)
Algiers [El Djazaïr], Algeria
Through all these projects, I held a cross-functional role consisting of:
• Cross-functional Data Engineer / Analytics role on Azure Cloud Data Platform in a Big Data environment.

• Development of automated ETL/ELT pipelines on Databricks (Python, SQL) to transform data into usable datasets.

• Collection, cleaning, and transformation of data from multiple sources (SQL / NoSQL / files / APIs).

• Automation of processing and data updates via scheduled workflows (orchestration).

• Ensuring data quality and producing insights for BI / steering.

• Business/technical collaboration up to production deployment, with containerization.
Databricks Microsoft Azure Python SQL Big Data
COSIDER OUVRAGES D'ART - CONSTRUCTION ET TRAVAUX PUBLIQUES,
Data Engineer
CIVIL ENGINEERING
September 2021 - September 2024 (3 years)
Algiers [El Djazaïr], Algeria
At Cosider Ouvrages d'Art, I worked on cross-functional data projects covering finance, human resources, construction (projects and public works) data, as well as equipment and heavy machinery data. The main objective was to structure, validate, and leverage project data to improve financial, operational, and strategic steering of construction activities.

The work focused on the exploitation and centralization of data from several key areas:

• Finance & Projects Data: budgets, costs, commitments, consumptions, variances.

• HR Data: resource allocation, workforce tracking, and charges per project.

• Construction / Public Works Business Data: project progress, production indicators, operational tracking.

• Construction Equipment & Heavy Machinery Data: availability, usage, costs, and performance.

Architecture & Global Approach
• Contribution to a Data Lakehouse / Data Warehouse architecture to centralize multi-source data and make it scalable.

• Structuring data flows according to Medallion Architecture logic (Bronze / Silver / Gold):

• Use of Databricks as a processing and industrialization environment for data pipelines.

• Development of transformations with Spark / PySpark, SQL, and Spark SQL to process data volumes and harmonize structures.

• Implementation of ELT/ETL transformations with modular logic (including dbt transformations for the analytical layer).

• Orchestration of pipelines and job dependencies with Airflow (scheduling, automation, monitoring).

• Provision of usable data in BI dashboards (operational reporting and decision support).

• Design of financial Data Marts and feeding BI dashboards for budget steering and variance tracking.
Databricks SQL Spark Airflow Python

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Master of Science
INSEEC,
2025
MSc 2 en Data Science & Analytics
Master in Big Data Analytics
Université de Badji Mokhtar,
2019
Master en Big Data Analytics