Freelancer profile translated to English.

Description

**Passionate about data and new technologies**, I evolve in an increasingly connected world where data has become a major strategic lever. **Convinced that data is one of the most valuable assets of organizations**, I support companies in its collection, structuring, and enhancement in order to transform information into concrete decisions and a competitive advantage.

Data Engineer with over 5 years of experienceand data projects carried out in various sectors, I design and industrialize modern data platforms capable of ingesting, transforming, and exploiting large volumes of data from various sources (APIs, files, web scraping, business systems).

**Specialized in the design of Data Platforms and the construction of robust and scalable ETL/ELT pipelines**, I develop reliable data architectures that allow business and analytical teams to fully exploit their data assets.

I intervene in particular on:

- Design of Data Pipelines and Data Platforms (Data Lake / Data Warehouse / Lakehouse)

- Data transformation and modeling

- Industrialization and orchestration of processing

- Implementation of automated cloud infrastructures

What sets me apart

1. End-to-end data vision

I intervene on the entire value chain: ingestion, transformation, modeling, orchestration, and deployment, in order to build truly usable data platforms.

2. Business impact-oriented approach

I start from business needs and KPIs to produce data useful for decision-making and analysis, not just technical solutions.

3. A transversal data profile

My experience in Data Engineering, Data Science, and Business Intelligence allows me to design data solutions that are both technically robust and adapted to analytical needs.

Industry field of expertise

Languages

English
Fluent
French
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

Canton de Vaud
Data Engineer
PUBLIC SECTOR
October 2022 - Today (3 years and 10 months)
Lausanne, Switzerland
Within the R&D team, I contribute to the development and evolution of the data platform used to centralize, transform, and exploit business data to support analysis, operational monitoring, and decision-making.

Main responsibilities:

- Design, development, and maintenance of data pipelines (ETL/ELT) for processing large volumes of data with Spark and Python.

- Management of the migration of historical ETL (SSIS) to a modern data platform based on Apache Spark and Airflow.

- Data modeling and structuring in a Data Warehouse, with the implementation of good data governance and quality practices.

- Design and monitoring of analytical and monitoring dashboards with Power BI and Grafana.

- Deployment and management of containerized services for data tools with Docker and Kubernetes.

- Implementation and management of data infrastructures via Infrastructure as Code (Terraform) to automate environments (databases, data tools, pipelines).

- Contribution to improving the reliability, supervision, and performance of the data platform.

Technical environment: Spark, Python, SQL, Airflow, Prefect, Azure (DevOps, Entra ID, Synapse), Power BI, Grafana, Kubernetes.
ETL Python Microsoft Azure Apache Spark Microsoft Power BI
ORANGE
Data Engineer
TELECOMMUNICATIONS
September 2020 - September 2022 (2 years)
Paris, France
Within the Mobile Service Expertise department, I contributed to the enhancement and exploitation of data from mobile services to improve performance monitoring and service quality.

Main responsibilities:

- Data Engineering: identification and definition of business KPIs, analysis and improvement of data quality, design and implementation of ETL pipelines for ingesting and transforming batch and real-time data, optimization of SQL queries and distributed processing.

- Data Modeling: structuring and modeling data for analysis, reporting, and visualization needs.

- Data Visualization: design and maintenance of analytical dashboards with Tableau and Google Data Studio, making datasets available to facilitate indicator tracking and decision-making.

- Data Science: exploration of Machine Learning use cases, data preparation and exploration (data exploration, feature engineering), design and experimentation of predictive models to identify service improvement levers.

Contribution to data enhancement and industrialization of analyses for business teams.

Technical environment: Spark, Python, SQL, Hive, GCP, Git, Tableau, Google Data Studio, TensorFlow, scikit-learn.
ETL SQL Python Apache Spark
Mercedes benz
Big Data & BI Project Manager
AUTOMOBILE
September 2019 - August 2020 (1 year)
Paris, France
Within the Data Warehouse team, I managed projects related to data enhancement and the modernization of analytical platforms, addressing Big Data, BI, and data governance issues.

Main responsibilities:

- Big Data:
Design and execution of a Data Lake Proof of Concept in a Hadoop and Microsoft Azure environment to centralize data and enable advanced analysis for Sales teams.
Identification of analytical and predictive use cases, data mining.
Implementation of initial analyses and visualizations to leverage collected data.

- Business Intelligence:
Management of a BI functional module redesign project in an IBM Cognos environment.
Design of analytical reports and dashboards for performance monitoring and statistics production.
Optimization of user access and rights management to improve data governance and security.

Technical environment: Hadoop, Microsoft Azure, IBM Cognos, Oracle, SQL, data visualization tools.
SQL Business intelligence Microsoft Azure