Freelancer profile translated to English.

Description

Data Architect & Lead Data Engineer with 10+ years of experience, I support companies in the design and industrialization of scalable cloud data platforms (GCP / AWS/Azure).

Specialized in Big Data and distributed architectures (Spark, BigQuery, Airflow), I tackle complex issues: HDFS to cloud migration, high-volume pipeline optimization, analytical modeling, governance, and performance.

I combine technical expertise with a product vision: my goal is not only to build pipelines but to create robust, maintainable, and business-impact-oriented data platforms (performance marketing, advanced analytics, ROI optimization).

Accustomed to demanding environments, I collaborate with Data, Marketing, and IT teams to deliver reliable, documented, and sustainable solutions.

Industry field of expertise

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Remote only

Primarily works remotely

HAVAS
Tech Lead Data Engineer / Cloud Data Architect
PRESS AND MEDIA
January 2025 - Today (1 year and 5 months)
Puteaux, France
Responsibilities & Achievements:
Design and evolution of the Converged Data Factory on Google Cloud Platform.
Development of SEA (Causal Impact) application.
Structuring of BigQuery datasets (raw / staging / mart / premium_facts).
Implementation of architectural best practices (partitioning, clustering, cost control).
Progressive migration of on-prem flows (HDFS / Hive / Parquet) to BigQuery.
Development of Spark pipelines (Scala / PySpark) for high-volume ingestion and transformation.
Implementation of batch & near real-time pipelines for marketing data (SEA, SEO, CRM, DV360, Salesforce).
Performance optimization (broadcast join, shuffle tuning, cache, Kryo serialization).
Automated SQL Server → BigQuery ingestion (Compute Engine / service accounts).
Workflow orchestration via Apache Airflow.
Analytical modeling focused on performance marketing (premium_facts tables, serps_data…).
BigQuery query optimization (cost reduction & execution time).
Implementation of models adapted to BI & reporting needs (Looker / performance dashboards).
GCP IAM & service accounts management.
Implementation of data quality controls.
Monitoring and improvement of pipeline reliability.
Contribution to DevOps & CI/CD best practices (GitLab pipelines).
Cross-functional collaboration with Marketing, Data Analysts, and IT teams.
Technical support and mentoring on Big Data best practices.
Google Cloud Python SQL Data Engineer Data Modeling & Performance Optimization
ENEDIS
Tech Lead Data Engineer
ENERGY AND UTILITIES
October 2023 - September 2024 (11 months)
Courbevoie, France
Mission:Lead a team, develop, and deploy the Customer Targeting project.

Implementation of development best practices.
Control and verification of data quality.
Responding to various business needs.
Development of PySpark processing scripts for different information systems (IS).
Development of Bash scripts for automation.
Automation of PySpark jobs via Apache Airflow.
Implementation of monitoring scripts.
Implementation and application of security standards via KYSS for the entire customer targeting project.
Refactoring and optimization of processes (PySpark, Python, Bash scripts).
Development of overall project documentation.
Management and enrichment of a PostgreSQL database.
Populating, persisting, and historizing data in HDFS.

Technical Environment:

HADOOP, SPARK, PYTHON, POSTGRESQL, SQL, MOBAXTERM, GITLAB, BASH SCRIPT, VSCODE, PYSPARK
Hadoop PySpark Python PostgreSQL SQL
LVMH
Senior Data Engineer
FASHION AND COSMETICS
February 2022 - October 2023 (1 year and 8 months)
Paris, France
Mission:Populate Marketing Target & Marketing Campaign Applications.

Development of Spark jobs for data stream processing.
Refactoring and optimization of processes in Scala and Spark.
Refactoring and optimization of code for the Marketing Target and Marketing Campaign projects.
Creation and monitoring of a dashboard for job monitoring, using Scala and Microsoft Teams.
Creation of automations on Salesforce.
Scheduling of workflows (Scala jobs) on Airflow.
Continuous integration with Jenkins.
Migration of data from Onedata (HDFS) to Google Cloud Platform (GCP), including modeling, construction, and population of the Data Product in BigQuery.
Integration and training of new Junior Data Engineers within the team.

Technical Environment:

HADOOP, SPARK, SCALA, JENKINS, MYSQL, SQL, SALESFORCE (MC, AUDIENCE), BITBUCKET, ELASTICSEARCH, INTELLIJ, POSTMAN, JUPYTER NOTEBOOK, BASH SCRIPT, BIGQUERY
Hadoop Spark Scala SQL Airflow