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Ikel O.IO

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About Ikel

Data Engineer & Data Analyst with 2 years of production experience, I work on the entire data chain: building cloud-native pipelines (AWS, Snowflake, Airflow, PySpark), modeling, analysis, and reporting via actionable dashboards (Power BI).
Experience in integrating generative AI solutions (RAG, LangChain) and in advanced analytics (RFM customer segmentation, KMeans clustering).
Graduated from a Master's in Big Data & ML — EFREI Paris (2025).
  • French

    Native or bilingual

  • English

    Fluent

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

Experience

  • Generali
    Data Engineer
    August 2023 - September 2025 (2 years and 1 month)
    Paris, France
    Design and industrialization of the marketing data chain, from source ingestion to indicator monitoring by business teams.
    Design and development of a marketing performance measurement tool in a big data environment (Hadoop, Snowflake): definition of indicators with business teams, data set modeling, and reporting.
    Development and automation of the data processing chain using PySpark, Snowpark, Python, and Dataiku: multi-source ingestion, transformation, quality control, and data availability for CRM teams.
    Calculation and monitoring of marketing KPIs (conversion rate, open rate, churn, retention), reported via dynamic Power BI reports enabling teams to autonomously monitor their performance.
    Analysis and behavioral segmentation of customers (purchase history, digital traffic, campaign engagement) to refine Salesforce campaign targeting and identify high-potential segments.
    Production of statistical analyses and actionable recommendations for business teams: RFM segmentation, engagement scoring, campaign impact measurement.
    Environment: Snowflake, Hadoop, PySpark, Snowpark, Python, Dataiku, SQL, Power BI, Salesforce, Airflow, Git
    Python Spark Snowflake Microsoft Power BI Advanced SQL
  • WeAreMUSH
    AI Data Engineer
    February 2026 - May 2026 (3 months)
    Paris, France
    • • Design and deployment of a RAG (Retrieval-Augmented Generation) architecture: vector indexing, semantic retrieval, and generation via OpenAI GPT-3.5 for a chatbot specializing in ecological transition.
    • • Structuring and preparation of the document corpus: cleaning, chunking, data quality evaluation, and LangChain pipeline optimization for accurate and relevant responses.
    RAG Generative AI Machine learning

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Education

  • Big Data & Machine Learning
    Efrei Paris
    2025
    Data Engineering, Statistiques et ML, Deep Learning, Data Lakes, Cloud Computing
  • Computer Science
    Asia Pacific University
    2023
    Réseaux et Protocoles, Systèmes d'exploitation, Architecture informatique

Certifications

  • Snowflake Data Engineering
    Snowflake
    2026
  • AI Fundamentals and the Cloud
    Amazon Web Services
    2026

Skill set

Categories