Johann B.
Data Engineer
Salaire / Taux journalier
Paris, France
Freelance, ouvert au CDI
Peut venir sur site
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À propos
Introduction
Data Engineer with 3+ years of experience building scalable data pipelines and growth analytics solutions. Led ETL transformations and cloud infrastructure projects at fast-growing companies like Pigment and Ankorstore using GCP, dbt, and Python. Specialized in turning complex data into actionable insights that drive business growth.
Expérience de travail
Data Engineer
Shadow
janv. 2025 - Présent
1 an 10 mois
Paris, France
Growth Engineer
Pigment
mai 2023 - janv. 2025
1 an 9 mois
Paris, France
Skills: Google Cloud Platform (GCP) · dbt · Extract, Transform, Load (ETL)
Growth Engineer
Ankorstore
sept. 2021 - mai 2023
1 an 9 mois
Paris, France
Skills: Google Cloud Platform (GCP) · dbt · Extract, Transform, Load (ETL)
Chrome Extension Developer
Data Driven Analytics
mai 2021 - août 2021
4 mois
Remote, Oregon 97458, États-Unis
Built and published a custom Google Chrome extension using Javascript to boost the user's outreach on social networks. The extension is a productivity tool to get the followers count of each hashtag by hovering, typing, or using an additional search box.
Data Science Fellow
General Assembly
déc. 2020 - mars 2021
4 mois
Greater Boston
Participated in a full-time immersive, 3 month data science course, completing in-class projects, personal projects, and hackathons focused on real-world applications of data science principles and best practices. Developed a portfolio of individually and collaboratively focused in-class projects: - Web APIs and NLP: Collected 4000 posts from two subreddits, r/AskMen and r/AskWomen using an API. I Then used natural language processing to train a classifier on which subreddit a given post came from. I used various libraries like pandas, seaborn, scikit-learn, NLTK and two models (Logistic regression, Random forest) - Song Recommender: Found a 28000 songs dataset with their characteristics such as tempo genres, duration, danceability and more... Then built a content-based recommender using cosine similarity that takes the title of a song and return a list of the 10 most similar songs. Libraries used: Numpy, Pandas, Seaborn, Scipy, Plotly, Sklearn
Formation
General Assembly
Data Science Immersive
2020 - 2021
1 an 1 mois
Suffolk University
Bachelor of Business Administration - BBA