Camille Lebrun
Data Consultant & Analytics Engineer | Data Engineering & Analytics Engineering Missions | Available in Toulouse and Remote | Expert Modern Data Stack
3+
Years crafting modern data stacks
+8h
Weekly reporting time saved per project
5+
Custom data stacks deployed end-to-end
About
About
I am Camille Lebrun, a Data Consultant and Analytics Engineer based in Toulouse, France. With a dual scientific and data background (Msc in Biochemistry and Master's in Data & AI), I have 3+ years of experience as an Analytics Engineer and Data Consultant . Specializing in Data Engineering and Analytics Engineering missions, I work with clients remotely across France and internationally.
I leverage technical versatility with the Modern Data Stack (Python, SQL, dbt, BigQuery, Airflow, Kestra, data visualization) and passion for the profession to best understand my clients' needs and challenges. I can effectively support them in their data valorization projects.
Curious and adaptable, I excel at selecting the right data tools and architecture while remaining a hands-on contributor. I focus on translating complex business needs into robust, autonomous technical implementations within a team.
Functional Domains
Projects
Recent projects
Modern Data Foundation & Orchestration
Medallion architecture with Kestra orchestration and Airbyte ingestion. Modular dbt models, data quality framework, delivered across 3 industries.
Marketing Analytics Platform Migration
Technical lead for migration from Dataroma to Modern Data Stack. Multi-source integration, dbt standards, and client team training.
Berlioz - Personal Project
AI nutrition assistant for cats using RAG, OCR label reading, and semantic search over a veterinary knowledge base.
Skills
Modern Data Stack Expertise
dbt
BigQuery
Airflow
Kestra
Python
Airbyte
dlt
Data Studio (formally Looker Studio)FAQ
Frequently Asked Questions
How do you orchestrate a data platform ready for business teams?
I orchestrate data platforms through source audit, medallion modeling, dbt and BigQuery pipelines, then fast delivery to Data Studio (formally Looker Studio), Power BI or Streamlit for day-to-day consumption.
How do you guarantee the reliability of pipelines and dashboards?
I ensure reliability through automated dbt tests, Slack/Cloud Monitoring alerts, anomaly detection via custom SQL, and volume/freshness guards on every critical table.
Can you optimize an existing stack without starting from scratch?
Yes, I launch with a technical audit, identify quick wins (dbt refactoring, partitioning, cost controls) and document an actionable roadmap for Modern Data Stack optimization.
Which KPIs prove the impact of your data missions?
I measure impact through incident detection time (-90%), hours saved in reporting (+8h/week), data reliability (green tests) and dashboard adoption metrics.
How do you collaborate with product, marketing, or ops teams?
I collaborate through intent workshops, accessible documentation, governance rituals, and ongoing support to keep metrics and alerts transparent for all stakeholders.
Which tools do you prioritize for orchestration, governance, and reliability?
I prioritize Kestra/Airflow for orchestration, dbt for modeling, Airbyte/dlt for ingestion, Power BI or Data Studio (formally Looker Studio) for KPIs, plus Python scripts for validation and monitoring in Modern Data Stack implementations.
Blog
Latest Articles
Apr 18, 2026
I Built a RAG for my family’s cat. Here’s what the real work looks like.
A real use case, a strict grounding constraint, and what building it actually taught me. Berlioz & Belioz Our family cat Berlioz was diagnosed with Chronic Kidney Disease. The vet left without...
ReadMar 26, 2026
Data architecture: stop worrying about names, start worrying about functions
Photo by Viktor Talashuk on Unsplash In french we say “Dans les vieux pots on fait les meilleures soupes” Why medallion architecture is a cloud-native rebrand of ODS and Data Warehousing —...
ReadMar 22, 2026
Your GROUP BY is lying to you: 5 window functions that reveal the truth
Photo by R Mo on Unsplash Every week, an analytics engineer somewhere ships a dashboard showing an Average Order Value of $150. Their CEO makes decisions based on it. Their median order...
Read