supriya jose

I'm building SQL- and Python-based ELT pipelines and self-service reporting for Chick King New Zealand, supporting approximately 40 retail locations. I maintain audit-ready datasets and resolve pipeline, data-quality, and tooling issues before they affect reporting.

I built Power BI and Excel/Google Sheets reporting across 300K+ transactions, using DAX, Power Query, and AppScript automation to give stakeholders decision-ready performance visibility. I also translate ambiguous commercial questions into structured analysis and scenario testing.

Through roles at the University of Canterbury, Pentagon Studio, and South Indian Bank, I've developed ETL workflows with dbt and Airflow, applied GCP/BigQuery analytics, investigated data-quality issues, and communicated findings to technical and non-technical stakeholders.

My projects combine data engineering and applied machine learning, including a flight-delay prediction tool using XGBoost, Random Forest, and SHAP, plus a multilingual translation pipeline using PyTorch, Hugging Face Transformers, AWS S3, and Lambda.