SAP BW/4HANA data engineer with 3 years of production delivery on enterprise-scale data warehouses at Infosys (CMA CGM) and hands-on aviation data engineering experience at OpenAirlines. Advanced Master's in AI & Business Transformation from ISAE-SUPAERO, bringing a cross-disciplinary edge across SAP data platforms, aeronautical domain knowledge, and applied AI to data transformation programs.
- Built a modular Python validation framework that automated flight data quality checks across aircraft datasets prior to ingestion into the fuel efficiency platform SkyBreathe®.
- Designed validation rules covering schema compliance, signal anomaly detection, and statistical trend analysis (pandas, NumPy) — translating aeronautical domain knowledge into quality KPIs tracked across airline datasets.
- Replaced a manual sign-off process with an interactive dashboard, reducing review effort by ~50% — enabling onboarding for Nippon Cargo Airlines and supporting data investigations for TAP Air Portugal and Atlas Air.
- Delivered end-to-end commercial reporting solutions for CMA CGM on a hybrid SAP BW/4HANA and Native HANA platform, processing 50–80M records daily.
- Covered the data lifecycle: modelled InfoProviders and ADSOs, built ETL pipelines, Calculation Views, CDS Views, ABAP and AMDP routines — delivering a unified reporting layer across SAP and non-SAP sources.
- Optimised process chain performance by ~55% (11h → 5h) through parallelisation and transformation restructuring. Reduced Qlik extraction time from ~5h to ~2h by migrating ADSO-based models to Native HANA Calculation Views.
- Collaborated with business stakeholders — supporting UAT for 25+ reports and dashboards across SAP Analytics Cloud, Analysis for Office, and Qlik for global commercial sales teams.
- Established daily data quality monitoring scripts and conducted root cause investigations to ensure accuracy of CRM and sales target reporting.
End-to-end medallion pipeline (Bronze → Silver → Gold) on Databricks using PySpark, Delta Live Tables, and Unity Catalog — enforcing data quality at each layer via DLT native expectations. Implemented rolling z-score anomaly detection via Spark window functions to surface sensor degradation patterns. Delivered a KPI monitoring dashboard and a 15-check data quality audit framework for full pipeline observability.