Issa SANOGO

- Analyze business data needs and legacy customer databases to understand and structure heterogeneous, high-volume data sources. - Improve, maintain and extend ETL pipelines (Airflow, Python, SQL) ensuring robustness, unit testing, full lineage/traceability and automated detection of data inconsistencies. - Collaborat with the platform squad, product teams and business experts to clean, transform and model data, and to ensure continuous evolution of the product database.

- Built and managed databases to enhance data reliability, quality and accessibility, while optimizing CRM processes and business automations. - Defined and implemented data integration workflows and pipelines to structure, clean and standardize incoming customer data. - Contributed to the company’s data architecture (modeling, management rules, documentation) and supported data governance with Product and IT teams. - Monitored data system performance and applied technical adjustments to ensure accuracy and consistency. - Created automated marketing and sales dashboards (Looker Studio, Tableau) and documented data sources. - Led follow-up meetings with clients and supported teams in adopting data tools and best practices.

- Diagnosed existing clinical and research data sources (patient records, biological samples, program outcomes) and defined data remediation and improvement plans. - Designed and implemented a full data warehouse, including the development and orchestration of ETL flows. - Identified new strategic datasets and aligned data collection with organizational goals. - Built dashboards and analytical tools based on medical and operational requirements. - Oversaw the evolution and reliability of data tools and infrastructure. - Supported medical staff, paramedics and researchers in data modeling to ensure usability and consistency. - Defined and operationalized data management rules, governance principles, and quality controls. - Implemented automated checks and alerts to ensure data consistency, accuracy, and compliance.

- Drafted data management and validation plans, and designed CRFs/eCRFs. - Managed and administered clinical databases: query programming, data cleaning, reconciliation between clinical and vigilance datasets, and preparation of data review meetings before database freeze. - Performed data archiving, produced data management reports, and conducted descriptive analyses and visualizations. - Developed dashboards, reproducible reporting tools, and automated workflows through a dedicated R package and Shiny applications.