Data Engineer | Fintech & Healthcare | Python · SQL · Snowflake · dbt · Airflow · AWS · Terraform · FHIR
8+ years delivering data systems across regulated environments — production pipelines, cloud-native architecture, and compliance-grade testing — in fintech, capital markets, and healthcare.
Proprietary AI builders generate a +92.0% Sharpe ratio premium over third-party integrators (Spearman ρ = +0.800, p ≈ 0.005) across 10 major tech stocks — visualized in an interactive Power BI dashboard.
| Pipelines | 4 production Airflow DAGs — stocks, SEC EDGAR 10-K, FRED macro, analysis |
| Storage | Hive-partitioned S3 data lake · Parquet/Snappy · Glue catalog · serverless Athena |
| Quality | 184 pytest unit tests · moto AWS mocking · GitHub Actions CI/CD |
| IaC | End-to-end Terraform |
Classifies 257K denied claims by root cause — systematic denials vs. documentation failures — and the remediation path differs fundamentally for each.
| Stack | Synthea FHIR R4 · Python · Snowflake (RAW → staging → mart) · dbt · Dagster |
| Scale | 495K total claims · 51.9% denial rate · 12 dbt models · 83 automated tests |
| RWE | T2D/CKD cohort · 104 patients · 54.8% metformin utilization |
