Freelancer profile translated to English.

Description

Curious and passionate, I enjoy exploring new fields, which led me from robotics to Data Science, and finally to Data Engineering.

With experience in various sectors, I specialize in designing scalable, efficient, and innovative solutions, leveraging the power of GCP and dbt to tackle complex business challenges. Currently, I am looking for an opportunity as a Tech Lead or Senior Data Engineer/Analytics, particularly on the Airflow/GCP/dbt stack. Continuously learning, improving skills on new technologies to meet specific client needs is also a source of motivation for me.

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Paris (up to 50km)

Sfeir
Lead Data Engineer
August 2023 - November 2024 (1 year and 3 months)
Paris, France
Moët Hennessy Financial team
- Leading and upskilling a team of 4 data engineers on finance and HR-related projects
- Technical referent and data solution architect on the Airflow, BigQuery, and dbt stack
- Deploying, optimizing, and maintaining large-scale data pipelines, with testing and monitoring (Elementary)
- Contributing to the evolution of Moët Hennessy's data platform
- Aligning data solutions with business needs, particularly for financial analysis (Profit & Loss, Stock valuation) and HR insights.
- Creating a structured training program to upskill individuals on data topics and make them operational
Sfeir
Data Engineer
October 2021 - July 2023 (1 year and 9 months)
Paris, France
Solocal Client insight team
- Optimizing and maintaining data pipelines using the Airflow, BigQuery, and DBT stack.
- Usage of elementary for testing and monitoring.
- Implementing business rules to enhance client insights, including turnover, seniority, and other key metrics, driving actionable data outcomes.
StarCLay
Data Scientist
June 2018 - October 2021 (3 years and 4 months)
Île-de-France, France
LexisNexis
• Find the paragraphs of appeal court decisions (unstructured text) where the judge made a decision Used model: Bi-LSTM + CRF (in Pytorch)
• Determine the outcome of case law decisions from courts of appeal: Used model: ULMFit from fast.ai
• Anonymization of legal decisions: Find surnames and adresses Used model: Spacy NER June 2018 - October 2018: Ponant (Cruise company based in Marseille)
• Revenue Management automatization: Prediction model for daily discount of cruise trips using temporal data. (Experiments with different machines learning models such as LightGBM and RNN)
• Training Ponant's employees on machine learning (how to do machine learning, usage of algorithms).