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Nacer Benyoub

@nacerbenyoub

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Data engineer transforming raw data into reliable, automated pipelines and insights.

Algeria

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What I'm looking for

I seek roles building automated, production-ready data pipelines and analytics solutions at companies that value clean architecture, reproducibility, and collaborative problem-solving.

I am a data engineer and Computer Science graduate with hands-on experience designing and automating end-to-end data pipelines. I focus on turning raw, unstructured data into actionable insights for stakeholders.

In a recent project I designed and deployed a fully automated ETL pipeline to explore Algeria's job market, ingesting live data from major job platforms and standardizing multilingual formats for consistent analysis.

I modeled data using a dimensional star schema within a medallion architecture, loaded processed data into PostgreSQL, and powered interactive dashboards in Metabase. I orchestrated ETL with Mage, version-controlled with Git, scheduled via GitHub Actions, and containerized with Docker for reproducibility.

I hold a Master's in Intelligent Systems for Knowledge Extraction and a Bachelor's in Computer Science, and I apply transfer learning and classical ML techniques to real-world problems while prioritizing maintainability, automation, and clear communication.

Experience

Work history, roles, and key accomplishments

Data Engineer

Nacer Benyoub

Designed and deployed a fully automated ETL pipeline for Algeria's job market, ingesting live listings, cleansing and modeling data into a dimensional star schema, and loading into PostgreSQL to power Metabase dashboards; orchestrated workflows with Mage and GitHub Actions and containerized with Docker.

Python ETL Web Scraping PostgreSQL Data Modeling Docker Mage GitHub Actions Pandas Data Warehousing

Education

Degrees, certifications, and relevant coursework

Université de Ghardaïa

Master's Degree, Intelligent Systems for Knowledge Extraction

Master's in Intelligent Systems for Knowledge Extraction with applied transfer learning to classify MRI data into three Alzheimer's disease categories, achieving high experimental accuracy.