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Azeddine B.AB

Azeddine B.

Senior Data Engineer

310 €/jour
Bonn, DE
8-15 ans

Délai de réponse moyen : 1h

À propos de Azeddine

Innovative Senior Data Engineer with 7 years of experience in designing and implementing robust data solutions that drive operational excellence and enhance data quality within organizations. Proficient in data engineering, data modeling, and big data processing, with a strong focus on leveraging Azure, Databricks, and Apache Spark technologies. Skilled in collaborating with cross-functional teams to develop scalable data architectures tailored to meet diverse business needs. Committed to applying advanced data techniques to extract meaningful insights and optimize processes, while continuously pursuing professional growth in the ever-evolving data landscape. Eager to contribute expertise to dynamic projects in a collaborative and forward-thinking environment.
  • Anglais

    Bilingue ou natif

  • Allemand

    Capacité professionnelle limitée

  • Arabe

    Bilingue ou natif

  • Français

    Capacité professionnelle limitée

Accepte de travailler sur site
Bonn (jusqu’à 50 km)

Expériences

  • LexisNexis Intellectual Property Solutions
    Senior Data Engineer
    AGENCE & SSII
    juin 2024 - Aujourd'hui (2 ans)
    Bonn, NW, Germany
    • Created data models and documented data flows to improve system architecture and data quality
    • Developed a data ingestion process to automate the transfer of data from multiple sources into a single database, resulting in a X% reduction in manual data entry
    • Utilized data visualization tools to create interactive graphical representations of financial data
    • Developed an enterprise data model that integrated data from multiple sources and enabled consistent data access across the organization
    • Led multiple teams and project to completion and with successful performance.
    Databricks SQL Python Microsoft Azure Elasticsearch
  • PatentSight - A LexisNexis Company
    Data Engineer
    août 2022 - juin 2024 (1 an et 10 mois)
    Bonn, NW, Germany
    • Developed big data pipelines in DataBricks in Azure utilizing medallion architecture that can handle +100 million full-text entries daily patent information.
    • Implemented CI/CD process for deploying DataBricks Jobs and pipelines, as well as maintaining and controlling permissions to our system via our control source.
    • Implemented big data processing pipelines using Spark and DataBricks for massive transformations in our medallion architecture (bronze, silver, gold).
    • Implemented a reference automated data monitoring system to detect and alert on data processing performances, that is currently being adopted at several departments and projects.
    • Implemented content processing pipelines on DataBricks for patent-related litigation content and deployed gold copies for sale on Snowflake marketplace and on Delta Share (ahead of Databricks' marketplace launch).
    • Designed and implemented Azure functions using event grids, storage accounts, and secrets. Implemented delivery pipelines using Azure DevOps and ARM templates.
    • Implemented a template system to be adopted for streaming pipelines that enabled syncing our Big DataBricks infrastructure with our Cloud SQL Server SSIS ETL.
    • Improved cost of multiple of our pipelines by factors of 10x (in some cases cost and performance optimization of more than 400%), utilizing spark best practices and better architecture.
    • Developed some internal tools to help automate some daily tasks using Python, Azure-CLI, Databricks-CLI, ElasticSearch querying, ..etc.
  • University of Koblenz and Landau
    Machine Learning Research Assistant
    novembre 2021 - mars 2022 (4 mois)
    Koblenz, Allemagne
    • Tutor 320+ Master’s students in machine learning and data mining python programming. The tutorials cover a wide variety of topics such as Clustering, Decision Trees, Random Forests, Linear Regression, Neural Networks, Data Transformation, and Interpretability. Assess students on their progress with the course by weekly assignments and final exams.
    • Extending on a novel multimodal German metadata extraction approach to improve the overall extraction accuracy from other state-of-the-art approaches. The improvements were achieved by employing transfer learning on a Natural Language Processing and an object detection model. The task employs using the following python machine learning libraries: Pytorch and TorchVision.

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Formations

  • Tools for Data Science Green Belt: Python Cyber Security Certificate Data Science Methodology Tools for Data Science Badge
    Tools for Data Science Green Belt: Python Cyber Security Certificate Data Science Methodology Tools for Data Science Badge
  • Master of Science
    University of Koblenz and Landau
    2022
    Master of Science

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