At IBM, I developed and maintained an incremental dbt serving-layer model in BigQuery to create a centralized order-level dataset for supply-chain and logistics analytics. I integrated data from purchase orders, shipments, warehouse receipts, and other sources.
For the H&M [Control Tower] project, I implemented planned-versus-actual lead-time calculations and deviation KPIs across supply-chain stages. I also handled data-quality scenarios and optimized processing with incremental dbt models, BigQuery partitioning, and clustering.
On IBM's D&B Analytics project, I developed and maintained GCP ETL/ELT pipelines and Airflow workflows. I performed data validation and production support, and provided curated datasets for analytics, reporting, and ML teams.
