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Lyes HLH

Lyes H

Supermalter

Data Engineer

€550/day
5 projects
Paris, FR
3-7 years

Average response time: 1 hour

Freelancer profile translated to English.
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About Lyes

Passionate about data engineering and new technologies, I have a strong capacity for analysis and synthesis. My technical skills allow me to design industrial solutions with innovative technologies.

Scope:
- Data processing: extraction, transformation, enrichment, aggregation, and loading
- Implementation of solutions that process various data sources
- Creation and maintenance of secure data pipelines
- Implementation of data consistency and quality controls
- Data ingestion into the Datalake
- Packaging of deliverables, project configuration and repository management
- Estimation of development costs
- Analysis and specification of needs
  • Arabic

    Native or bilingual

  • English

    Basic

  • French

    Native or bilingual

Can work on-site
Paris (up to 50km)

Experience

  • Crédit Agricole Corporate & Investment Bank
    Data Engineer
    BANKING AND INSURANCE
    October 2019 - December 2021 (2 years and 3 months)
    Saint-Quentin-en-Yvelines, France
    OMP (Mutualized Provisioning Tool) is a tool based on
    Moody’s Analytics that calculates provisions on outstanding bank loans for the various entities of the Crédit Agricole Group.

    - Implementation of data control processes.
    - Automation of data extractions after each
    calculation step of the workflow.
    - Automation of data ingestion into the DATALAKE.
    - Implementation of Talend processes.
    - Scheduling of processes.
    - Integration of calculation steps into the calculation workflow.
    - Packaging and deployment of solutions.
    - Analysis of requirements specifications.
    Talend DI Spark 2.2 Hadoop (HDFS) Java 8 SQL PL/SQL Git Maven 3
  • Crédit Agricole Assurances
    Data Engineer Consultant
    BANKING AND INSURANCE
    February 2022 - Today (4 years and 5 months)
    Redesign of regulatory declarations for
    the tax administration (DGFIP) and the FICOVIE retirement union: Annual, Retirement Savings Information, Automatic Exchange of Information

    - Quality and consistency control of data;
    - Extraction of declarations in XML format;
    - Data ingestion into the DATALAKE;
    - Implementation of Business rules;
    - Tracking of Workflow steps;
    - Scheduling of processes;
    - Management of project repositories;
    - Packaging and deployment of solutions;
    - Analysis of detailed functional specifications;
    Spark 2.2 Hadoop (Hive, Oozie, Hdfs) Java 8 Hive QL Shell Script Cucumber XML/XSD Jenkins Git Maven 3

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