Freelancer profile translated to English.

Description

Most data platforms fail not because of the technology itself. They fail due to design flaws, lack of ownership, and uncontrolled costs.

I help companies build and evolve their data platforms while optimizing Snowflake and BigQuery costs.

With over 8 years of experience, I have worked on complex data environments (banking, pharma, media) with large volumes and strong business constraints.

I manage the entire process, from design to production.

What I bring:

· End-to-end data pipelines (batch & streaming)

· Modern data stack (Snowflake, BigQuery, dbt, Airflow, Spark)

· Platform architecture (cloud, Kubernetes, CI/CD, Terraform)

· Data cost optimization (FinOps approach)

Typical impact:

· Processing data volumes at the TB scale

· Improving performance and reliability

· Reducing Snowflake / BigQuery costs (20–50%)

I build data platforms that scale technically and financially.

Industry field of expertise

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Paris (up to 50km)

GROUPE CCF
Senior Data Engineer
January 2023 - Today (3 years and 5 months)
Designed & Implemented:
Designed and implemented robust data pipelines for end-to-end data collection, ingestion, transformation, and storage using dbt for modeling and Snowflake for warehousing.
Platform Engineering: Architected and maintained the foundational infrastructure using container orchestration (Kubernetes) and infrastructure-as-code (Terraform), ensuring scalability, resilience, and seamless integration across diverse data pipelines.
Collaboration:
Partnered with data scientists, developers, and stakeholders to align technical solutions with business requirements.
Automation:
Built and maintained CI/CD workflows using Git, Jenkins, Maven, Docker, and Kubernetes significantly reducing deployment time.
Optimization:
Automated routine tasks with bash scripts and Terraform, reducing manual intervention.

Technical Environment:
AWS (S3, RDS, Lambda, Glue, Athena), Starburst, Airflow, DBT, Kubernetes, MSK, SQS, Python, Scala, GitLab CI, Terraform, Git
AWS Terraform Airflow starburst DBT
Servier Monde
Senior Data Engineer GCP
PHARMACEUTICALS INDUSTRY
July 2021 - December 2023 (2 years and 5 months)
Implementation of a datalake in R&D on data experimentation of laboratories for Servier biologists, chemists, pharmacologists.

RELEASES
- Complexity: a large volume of data (tens of TB) from screening machines and very complex business rules
- Implementation of batch data ingestion workflow
- Implementation of workflows for data cleansing and exposure

TECHNICAL ENVIRONMENT
Bigquery, Cloud Storage, DataFlow, Python, Argo, Kubernetes, Pyspark, Git, Terraform
Google Cloud Platform (GCP) Python SQL CI/CD BigQuery
Solocal
Senior Data Engineer GCP
ENTERTAINMENT AND LEISURE
November 2020 - May 2022 (1 year and 7 months)
Paris, France
Implementation of a data platform that integrates sales and vendor data and makes it usable by the various Finance and Compensation squads

RELEASES
- Complexity: Many data sources to integrate and various
data types (batch, streaming)
- Implementation of batch data ingestion workflow
- Implementation of streaming data ingestion workflow
- Implementation of workflows for data cleansing and exposure in the Data Platform

TECHNICAL ENVIRONMENT
Bigquery, Cloud Storage, Composer, Airflow, DataForm, Python, Java, Cloud Function, Pub/Sub, Git
Big Query Python SQL Google cloud Gitlab CI Linux scrum