Description

Most data platforms don’t fail because of technology.

They fail because of poor design, lack of ownership, and uncontrolled costs.

I help companies build or scale their data platform while reducing Snowflake and BigQuery costs.

Over the past 8+ years, I’ve worked on data platforms in banking, pharma, and media environments, handling large-scale data pipelines and complex business requirements.

I take ownership from design to production.

What I bring:

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

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

· Data platform architecture (cloud, Kubernetes, CI/CD, Terraform)

· Cost optimization (FinOps mindset applied to data platforms)

Typical impact:

· Pipelines processing TB-scale data daily

· Improved performance, reliability, and delivery speed

· Reduction of Snowflake / BigQuery costs (20–50%)

I focus on building data platforms that scale — technically and financially.

Available for remote engagements across the UK and Europe.

Industry field of expertise

Languages

English
Fluent
French
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

CCF
Senior Data Engineer
BANKING AND INSURANCE
January 2023 - Today (3 years and 5 months)
Paris, France
Long-term mission within a banking group to modernize the data platform and improve reliability in a regulated environment.

Designed and optimized end-to-end data pipelines (Snowflake, dbt, Airflow)
Built a scalable data platform (Kubernetes, Terraform, CI/CD) to industrialize deployments
Implemented data governance and data quality best practices
Optimized Snowflake usage (queries, dbt models, orchestration) to improve performance and reduce costs

→ Production pipelines used by multiple business teams

Stack: AWS · Snowflake · dbt · Airflow · Starburst · Terraform · Python · Scala · Kubernetes
Snowflake Python SQL Terraform Amazon Web Services
Servier
Senior Data Engineer
PHARMACEUTICALS INDUSTRY
July 2021 - December 2023 (2 years and 5 months)
Paris, France
Built from scratch an R&D data platform to centralize large-scale experimental data in a scientific environment.

Designed a scalable data platform handling tens of TB of experimental data
Developed batch ingestion workflows and complex data cleansing processes
Structured transformations with dbt to deliver reliable datasets for scientists
Collaborated closely with biologists, chemists, and researchers to align data with scientific needs

→ Platform directly used by R&D teams

Stack: GCP (BigQuery, Cloud Storage, DataFlow, DataProc) · dbt · Python · PySpark · Argo · Kubernetes · Terraform · Git
Google cloud Apache Spark Terraform BigQuery Python
SFEIR
Senior Data Engineer
CONSULTING AND AUDITS
April 2019 - June 2021 (2 years and 2 months)
Paris, France
Delivered data platform projects for multiple clients on GCP environments.

Solocal — Data Platform
Built a data platform integrating sales and vendor data for Finance and Compensation teams
Developed batch and streaming pipelines with strong data quality requirements

Les Echos / Le Parisien — Customer Data Platform
Implemented a multi-source Customer Data Platform to improve marketing performance
Integrated cross-brand customer data and exposed datasets to business teams

Stack: GCP (BigQuery, Cloud Storage, Composer) · Airflow · DataForm · Python · Java · Cloud Functions · Pub/Sub · Terraform · Git
Google cloud BigQuery Terraform DBT Python