Camille Lebrun
Data Consultant & Analytics Engineer | Data Engineering & Analytics Engineering Missions | Available in Toulouse 🧱 & 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
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 Missions
End-to-end data projects with measurable business impact
Product Analytics with GA4
GA4 data modeling across e-commerce and financial services using dbt and Dataform. Medallion architecture with specialized marts.
Modern Data Foundation
Medallion architecture with Kestra orchestration and Airbyte ingestion. Modular dbt models with automated quality framework.
Slack Monitoring System
Comprehensive Slack monitoring for dbt pipelines and business KPIs. Automated alerts and scheduled reporting.
Tech Stack
Modern Data Stack Expertise
dbt
BigQuery
Airflow
Kestra
Python
Airbyte
dlt
Looker StudioFAQs
Frequently Asked Questions
Enterprise-grade delivery practices and tooling choices.
How do you orchestrate a data platform ready for business teams?
You orchestrate data platforms through source audit, medallion modeling, dbt and BigQuery pipelines, then fast delivery to Looker Studio or Streamlit for day-to-day consumption.
How do you guarantee the reliability of pipelines and dashboards?
You 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, you 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?
You 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?
You 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?
You prioritize Kestra/Airflow for orchestration, dbt for modeling, Airbyte/dlt for ingestion, Looker Studio for KPIs, plus Python scripts for validation and monitoring in Modern Data Stack implementations.
Field Notes
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