Building scalable data pipelines and turning raw data into reliable, production-grade analytics, with Python, SQL, and cloud-native tools.
Experience
Education
M.Eng Software Engineering
Computer Science
Tech Stack
Projects
Designed an executive-facing credit risk dashboard analyzing a retail loan portfolio across delinquency stages, product segments, and vintage cohorts. Engineered DAX measures for PAR (portfolio-at-risk), roll rates, and net charge-off trends, with row-level security segmenting views by branch and risk tier. Surfaced early-warning signals that flagged rising delinquency in a specific segment ahead of standard monthly reporting.
Built an end-to-end medallion-architecture pipeline (bronze → silver → gold) ingesting transactional and clickstream data for a multi-store e-commerce dataset on Azure Databricks. Implemented incremental loads, schema enforcement, and data quality checks in PySpark, with orchestration via Azure Data Factory and curated Delta tables feeding downstream BI. Reduced full-refresh processing time through partitioning and incremental logic instead of reprocessing the entire dataset.