Freelancer profile translated to English.
Back to original languageAbout Louis
Analytics Engineer & Data Analyst
With 5 years of experience in tech environments (Microsoft, Aircall, Stuart, Too Good To Go), I help Data teams build solid foundations: reliable pipelines, tested and documented models, actionable data. I work with both Data Analysts and ML Engineers, always keeping an eye on the end-use of the data.
⭐️ My Goal
To enable your teams to rely on trustworthy and actionable data to confidently drive your decisions, without depending on a single person to understand it.
⚙️ My Expertise
- Robust and scalable pipelines: design and maintenance of modern data architectures on AWS and Snowflake, with dbt and Airflow -> from raw to analytical.
- Future-proof modeling: materializations adapted to volume, reusable macros, systematic testing, and careful documentation.
- Business enablement: metric definition, dashboard creation (Looker, Tableau, Superset), and training teams in data self-service.
🎯 Project Examples
- Standardization of data architecture for 16 retailers (Python + S3 ingestion, dbt raw & core models) — previous architecture deprecated in 4 months
- ML-ready pipelines for an in-store discount recommendation model -> +10% sales after one month
- Automated weekly performance reports for over 500 franchises (McDonald's, Burger King, Sushi Shop…)
- Multi-source marketing attribution model (Google Ads, Meta Ads, HubSpot, dbt)
- User experience tracking funnel and identification of friction points (Amplitude, Segment)
- Training business teams in data self-service
💡 My Skills
Transformation & orchestration: SQL, Python, dbt, Airflow, Airbyte, Fivetran
Cloud & Infra: AWS (S3, Glue, Redshift), Snowflake
Visualization: Looker, Tableau, Superset, Count
French
Native or bilingual
English
Fluent
Spanish
Fluent
Can work on-site
Paris (up to 10km)
Experience
- Too Good To GoAnalytics EngineerRETAIL (LARGE RETAILERS)June 2025 - May 2026 (11 months)Paris, France👉 Standardization of data architecture for 16 retailers (S3 migration, dbt raw & core models) -> deprecation of the old architecture in 4 months, reusable documentation to speed up future onboarding.👉 Design and delivery of two ML-ready pipelines (retail_price & item_outcomes) to feed a discount recommendation model: multi-retailer incremental dbt models via macros, custom quality tests, progressive deployment -> +10% sales on discounted products in-store.👉 Implementation of dbt best practices within the team: implementation of systematic tests (unique, not null, accepted values, custom SQL), documentation of existing and new models -> contributing to promoting a data culture and ensuring the long-term reliability of the codebase.
- StuartAnalytics EngineerLOGISTICS AND SUPPLY CHAINJuly 2024 - May 2025 (10 months)Paris, France👉 Implementation, maintenance, and deprecation of data ingestion pipelines (Intercom, Google Ads, Meta Ads, LinkedIn Ads, Salesforce, HubSpot, ...); creation of raw and core models in dbt, made available to Analytics teams for their analyses.👉 Improvement of a Twilio × backend ingestion allowing to link a package_id to the end-user's phone number -> opening up finer granularity to better understand users and refine persona definition.👉 Design and maintenance of Airflow DAGs to orchestrate complex data pipelines -> dependency management, alerting in case of failure, and continuous monitoring to ensure data flow reliability.
- StuartSenior Data AnalystLOGISTICS AND SUPPLY CHAINJanuary 2022 - June 2024 (2 years and 5 months)Paris, France👉 Automation of weekly performance report delivery per franchise for major clients (McDonald's, Sushi Shop, Burger King, ...): definition of metrics with sales teams, data modeling, dashboard design, and setup of automatic deliveries.👉 Execution of pricing analyses for contract renegotiations: financial and operational analyses, modeling of several pricing scenarios, presentation, and close collaboration with sales teams.👉 Standardization of visualization tools across the company: redefinition of key metrics, alignment with all business teams, creation of consolidated performance reports, and documentation of metrics.👉 Other projects: marketing attribution model (HubSpot, dbt, Google Ads, Meta Ads), customer retention analysis (churn), user experience tracking funnel (Amplitude, Segment), strategic analysis of end-user behavior presented to the French board.
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Education
- Data Science & Artificial IntelligenceLe Wagon2022Programme intensif de 6 mois à temps partiel pour apprendre la Data Science/Analyse/Engineering avec Python : • Analyse de données avec SQL, BigQuery, Pandas, NumPy et Matplotlib • Statistiques avec SciPy, Seaborn et Statsmodels • Machine Learning avec Scikit-learn • Deep Learning avec TensorFlow Keras • Développement de produits data avec Google Cloud Platform, MLflow, Flask, Heroku et Streamlit
- Master's degree in Information Systems ManagementIÉSEG School of Management20207ᵉ école de commerce en France (classement Financial Times) 21ᵉ Master in Management au monde (classement Financial Times) 3 400 étudiants 82 % de professeurs internationaux IESEG est membre de la Conférence des Grandes Écoles, de EQUIS, de l’EFMD (European Foundation for Management Development), de l’AACSB (Association to Advance Collegiate Schools of Business) et de la CLADEA (Consejo Latino Americano de Escuelas de Administración).
Certifications
- dbt Fundamentalsdbt Labs2026