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Ala Eddine C.AE

Ala Eddine C.

Senior Data Engineer / Analytics Engineer

700 €/jour
Paris, FR
3-7 ans

Délai de réponse moyen : 1h

À propos de Ala Eddine

An enthusiastic senior Data Engineer, who enjoys designing, building, and optimizing data pipelines that empower businesses to unlock actionable insights.


With expertise spanning cloud platforms (Azure / AWS), big data technologies (Databricks / Snowflake), and machine learning workflows (MlFlow), I help organizations to drive innovation by transforming raw data into strategic assets, while leading teams, implementing best practices, and ensuring seamless data operations in fast-paced environments.
  • Français

    Bilingue ou natif

  • Anglais

    Capacité professionnelle complète

  • Allemand

    Notions

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

Expériences

  • AXA France
    Senior Data Engineer
    BANQUE & ASSURANCES
    mai 2022 - Aujourd'hui (4 ans)
    Nanterre, France
    • Context:
    I was part of the Big Data team linked to the HR and Communication guild, where I worked on issues related to the manual management of the employee database for AXA France, including tracking employee inflows and outflows. The goal was to replace all manual processes with an automated solution using Databricks as the core technology.

    • Missions:
    - Design and development of cloud-based data solutions in Azure for HR department;
    - Generate Business Views used by data analysts in RH dashboards using pyspark;
    - Use Delta Lake to ensure data quality and reliability through ACID transaction management and schema validation;
    - Optimize PySpark jobs and resource allocation for each job;
    - Implement Domain Driven Design approach;
    - Use the TDD approach in order to ensure that your code meets the specified requirements and behaves as expected;
    - Line management and mentorship of a team of junior Data Engineers;
    Microsoft Azure Databricks PySpark Optimisation Lakehouse Azure Data Factory
  • Total Digital Factory SAS
    Data Engineer
    ENERGIE
    juin 2021 - mai 2022 (1 an)
    • Context:
    I worked within the Digital Factory entity, which handled all digital projects for TotalEnergies, organized in a squad-based structure. I worked on a project to automate the monitoring process for FPSO (Floating Production Storage and Offloading) platforms, which extract oil and gas offshore. The goal was to track the condition of machinery (pumps, engines) using temperature and pressure sensors, and to analyze weak signals in order to detect anomalies early on.

    • Missions:
    - Develop and optimize complex data pipelines to calculate heuristics for petroleum business;
    - Create DAGs of pyspark jobs using DBX databricks’s tool,
    - Use Autoloader to handle incrementally sensors uploaded data
    - Implement SCD type 2 strategy using delta lake functionalities in order to track spare parts orders from SAP
    - Develop code agilely and work in a fast-paced DevOps environment (You build it, You run it)
    - Collect, consolidate, enhance and model large volumes of data (Lakehouse / deltalake)
    Azure Databricks Microsoft Azure Terraform SQL/PLSQL Méthode agile autoloader Delta Lake Lakehouse SCD
  • Allianz Trade France
    Data engineer
    BANQUE & ASSURANCES
    décembre 2019 - mai 2021 (1 an et 5 mois)
    Puteaux, France
    • Context:
    I was part of the Data Foundation team within the DataHub, where the primary role was to manage the backbone of an event-driven architecture. This ensured smooth communication between data consumers and producers, while providing several services such as data archiving and historical data correction through the implementation of a data lake.

    • Missions:
    - Participate in the design and implementation of an Event Driven system using either object-oriented or functional programming techniques implemented in Python;
    - Collaborate with Software Engineering and System teams to drive cross function visibility and reduction of technical debt across the teams;
    - Craft and develop data integrations across platforms and data stores, providing systems, message brokers, and any required ETL pipelines;
    - Create an API that provides access to data at a specific point in time, allowing users to browse through historical records;
    Amazon Web Services AWS EMR REST APIs PySpark Event-driven architecture AWS Lambda Terraform Docker AWS ECS Réduction des coûts DynamoDB AWS Kinesis AWS Athena

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Formations

  • Engineer's Degree, IT
    télécom sudparis
    2018
    Main courses : - Complex Networks and validation. - Operating systems (multi-threading, multi-processing, memory management ...) - Artificial intelligence - Distributed Systems - Cloud and Infrastructure - Middleware for distributed applications - High Performance Computing - Semantic Web and Big Data infrastructure

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Compétences (46)

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