Principal Software Engineer
CurrentArchitected and delivered a 100% cloud native metric & log ingestion pipeline leveraging Distributed Eventhub (Kafka like), Stream analytics (Spark like), and Azure Data Explorer (Splunk like columnar store). Entire solution is deployed automatically via Terraform, including several components that aren't fully natively supported. (e.g. seamless Stream Analytics integration).Architected and implemented core pieces of a "lift and shift" solution for legacy metric and log ingestion pipeline from on-prem to cloud. Worked with various stakeholders for a hybrid solution that allows rest of DocuSign to transition from on-prem to cloud.Architected and implemented a visual "seasonality scaling" optimization algorithm and dashboard that allows all of DocuSign to see potential savings (80% across the company) from implementing seasonality based scaling. This required working with various disconnected sets of ambiguous data and partnering with teams across the company.This is helping drive how teams implement the transition to the cloud, with a potential 80% cost savings (14M+ a year)Architected and implemented an instantaneous PII mitigation solution on top of a dataset that doesn't natively support instantaneous deletions.Architected and implemented an "indexed" cold storage solution, leveraging existing cloud native solutions in a novel way, which deprecates an existing unindexed blob archive that isn't queryable. Reduced cost of an audit/scrub by tens of thousands of dollars each, and days of dev time. Unlocked the ability for new tables to be "backfilled" from cold storage, saving hundreds of thousands per table.Architected and implemented an ingestion solution for OpenTelemetry data in a columnar store without native support, with 100x faster performance at query time.Currently 500B rows, 9B rows/day, expected to scale to 100B rows/day, 3 trillion rows.Administer Docusign's IL4 USGOV metrics and logs platform. Passed NACLC and SSBI checks.