Projects

These projects illustrate how I work: understand the context, structure progressively, and deliver solutions that last.

Data Integration Platform Industrialization

Sector: Occupational Health (SaaS)

A SaaS company needed to integrate data from new clients across varied sources, with high volumes and strict reliability requirements.

What I did:

  • Client data migration from heterogeneous systems
  • Pipeline redesign to industrialize the integration process
  • Reliable ingestion implementation for high volumes
  • Technical decision-making with the platform squad
  • Coordination with business stakeholders and clients

Stack: Python, SQL, Airflow

EdTech Startup Data Structuring

Sector: Educational Technology

A growing company with data scattered across multiple tools, lacking consolidated vision or governance.

What I did:

  • Database construction and optimization
  • Integration pipelines: cleaning, standardization, structuring
  • Data architecture contribution: modeling, business rules
  • CRM governance and process improvement
  • Automated dashboards for operational tracking
  • Team enablement for data tool adoption

Stack: Python, SQL, MySQL, Looker Studio

Medical Research Data Warehouse

Sector: Research Institute (Healthcare)

A research institute with scattered data repositories: patients, biological samples, research data. Need to centralize, ensure reliability, and make data actionable for medical and scientific teams.

What I did:

  • Existing repository diagnostic and action plan definition
  • Data warehouse design and implementation
  • ETL workflow development
  • Strategic data needs identification with leadership
  • Dashboards for medical teams and management
  • Data tool and practice governance leadership
  • Medical and scientific team support

Duration: 3 years

Stack: Python, R, SQL Server, PostgreSQL, Tableau, Power BI, Docker

Clinical Trial Data Management

Sector: Public Hospital (AP-HP)

Clinical trial data management at France’s largest hospital system, with strict regulatory requirements.

What I did:

  • Complete clinical trial data management ownership
  • Database administration
  • Report development and automation

Duration: 4 years

Stack: R, MySQL

What these projects have in common

They share key characteristics:

  • Demanding contexts — Healthcare, medical research, sensitive data
  • Long-term vision — Multi-year engagements, not one-off interventions
  • Beyond technical — Business coordination, governance, team support