Freelancer profile translated to English.
Back to original languageAbout Abdeljalil
Data Engineer | Pipeline Automation & Databases (Casablanca)
Currently in my 4th year of engineering school (EMSI) specializing in Data Engineering and Infrastructure, I assist companies in extracting, transforming, and leveraging their data.
My approach is resolutely oriented towards "Industrialization": I don't just write scripts, I design robust and automated architectures. During my experience at Eurafric Information's IT department, I had the opportunity to design and deploy end-to-end data pipelines in a demanding banking environment.
My technical expertise:
- Languages & Databases: Python (Pandas, BeautifulSoup), SQL, PostgreSQL
- Data Engineering: ETL/ELT, Apache Spark, REST API integration, Hadoop
- Infrastructure & ML: Docker, XGBoost
Whether it's scraping complex data from the web, modeling a relational database, or automating tedious tasks, I deliver clean, documented, and optimized code.
Let's discuss your next data project!
English
Fluent
Arabic
Native or bilingual
French
Fluent
Remote only
Primarily works remotely
Experience
- EMSIEnd-to-End News Data Pipeline (Medallion Architecture)SOFTWARE PUBLISHINGJanuary 2026 - May 2026 (4 months)Casablanca, MoroccoDesigned and deployed an automated data pipeline using the Medallion Architecture to scrape, process, and visualize web data.Skills Acquired & Demonstrated:Data Extraction: Automated web scraping using Python and BeautifulSoup.Orchestration & Data Lake: Containerized the environment via Docker, using Apache Airflow to orchestrate ingestion into a MinIO Data Lake.ETL & BI: Transformed raw HTML into structured PostgreSQL tables, building interactive Business Intelligence dashboards with Metabase.
- Eurafric Information,Data Engineer InternDIGITAL AND ITJuly 2025 - August 2025 (1 month)Bouskoura, MoroccoDesign, development, and deployment of a complete end-to-end data pipeline for the automated processing of massive bank transaction files. This project demonstrates mastery of data industrialization, from raw ingestion to Business Intelligence readiness.Technical architecture implemented:Automated ingestion: Configuration of Apache NiFi flows to monitor, extract, and decompress local source files to a distributed file system (HDFS).Processing & Transformation: Writing distributed processing jobs with Apache Spark (via Python) to clean raw data, standardize schemas, and generate complex business aggregations (e.g., average outstanding amounts per city).Orchestration: Creation of Apache Airflow DAGs to reliably schedule, execute, and monitor Spark jobs via the SparkSubmitOperator.Analytical Storage: Loading cleaned data and aggregation tables into a Docker-contained PostgreSQL database, enabling instant analytical queries.
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Education
- Engineering DegreeEMSI2027Engineering Degree
- Baccalaureate in Physical SciencesGroupe Scolaire Addoha 22022Baccalaureate in Physical Sciences
Certifications
- Introduction to Big DataUC San Diego / Coursera
- Using Python to Access Web DataUniversity of Michigan / Coursera