Adrien Chabanel

- Designed an end-to-end data platform on AWS, replacing a fragmented ecosystem of manual reports with an industrialized ELT architecture that progressively became the reference analytical layer for business teams.

- Developed 30+ ingestion and transformation pipelines orchestrated with Airflow, including idempotency, backfills, error handling, alerting and quality checks, automating ~10 hours/week of manual data collection with a run success rate above 98%.

- Modeled 150+ dbt models using a medallion architecture approach, structured around staging, intermediate and marts layers, to harmonize key business KPIs.

- Implemented a data reliability framework including dbt tests, documentation, automated lineage and GitHub Actions CI.

- Developed an internal analytics web app using Apache ECharts, enabling the full migration of legacy Power BI dashboards to an internal solution, reducing BI licensing costs and generating ~€5,000/year in savings.

- Built and maintained the data flows powering 2 internal logistics and operations monitoring tools used daily by 30+ employees.

- Delivered in-depth analyses on growth levers including acquisition, conversion, sales performance and campaign effectiveness.

- Centralized and structured marketing data in BigQuery to build a reliable and unified analytics foundation.

- Harmonized KPIs across marketing, sales and customer data sources to reduce reporting discrepancies and improve decision making.

- Automated data marketing workflows for customer segmentation, CRM journeys and review collection.

- Designed and maintained a library of educational Python notebooks covering machine learning, statistics and data visualization.

- Led Data & BI masterclasses for student cohorts, making complex technical concepts accessible to non-expert audiences.

- Supported students on data projects, from problem framing to technical recommendations.