At Stripe, I build canonical payment lifecycle models and batch, streaming, and reconciliation pipelines for finance, risk, compliance, and merchant analytics. My work reduced reporting discrepancies by 35%, cut manual finance investigations by 45%, and improved risk-signal freshness from hours to minutes.
Previously at Uber, I operationalized real-time marketplace intelligence for pricing, fraud, incentives, and operations using Kafka, Flink, Spark, Hudi, Presto, and Pinot. I standardized lifecycle datasets, improved delayed-event accuracy, and enabled sub-minute visibility for high-priority operational workflows.
I've also built governed healthcare reporting at Quartet Health and fulfillment analytics at Amazon, turning complex event lifecycles into trusted, auditable datasets. I focus on data quality, reconciliation, lineage, performance, and reusable models that help teams make confident decisions.
