Côme Lescure

I’m an Analytics Engineer with 3+ years of experience turning raw data into reliable, actionable insights.

My work sits at the intersection of data engineering, analytics, and business strategy — ensuring that every stakeholder, from product to leadership, can make decisions based on trustworthy data.

I specialize in designing robust data models, building scalable pipelines (dbt, BigQuery, Airflow), and maintaining high-quality transformation layers aligned with business logic.

I also develop internal tools and dashboards in Python (Streamlit) and BI platforms (Looker, PowerBI, Metabase) to make complex data easily accessible.

I’ve led several data architecture redesigns at NielsenIQ, improving data reliability, performance, and time-to-insight for analytics teams across multiple markets.

Beyond the technical side, I bring a strong product mindset and a clear communication style that bridges technical and non-technical teams.

Core skills:

- SQL / BigQuery / dbt / Airflow

- Python (pandas, Streamlit, automation scripts)

- Data modeling & quality monitoring

- BI: Looker, PowerBI, Metabase

- Git / CI-CD / version control

- Data documentation & knowledge sharing

What I can help you with:

- Building or refactoring your analytics stack

- Structuring your dbt or Airflow pipelines

- Designing clean, scalable data models

- Automating QA and monitoring for data reliability

- Developing clear dashboards and decision-ready datasets

I’m passionate about building reliable, transparent, and efficient data systems that make analytics teams thrive.

Let’s talk if you’re looking for someone who can bridge data engineering and analytics — and make your data truly actionable.