I built and guided a team through a challenging cross-organizational initiative, successfully defining the parameters of control plane health. This contribution not only solved the complexity of health but also laid the foundation for more efficient and effective control plane operations.

* Developed and maintained a Golang Kubernetes service that defines health for Splunk Cloud control plane operations

* Designed a cross-organizational health service for Splunk’s Observability platform making SignalFx/Prometheus/Logs health data highly actionable by automated processes

* Made our observability ingestion platform directly actionable for automated health purposes

* Built a health check that removed 91% of manual touchpoints for all new automatically delivered Splunk stacks

* Designed an upgrade health check that saved 30k engineering hours per year

* Engineered health checks enabling Splunk to expand into GCP acquiring over 200 net new customers

* Designed and enforced SRE best practices for uptime and alerting within our team

* Ran the hiring working group and enabled 120+ interviews and 21+ hires

* Hired and built a highly productive team with a growth oriented engineering culture

* Designed internal on-call, Scrum, and culture documents and encouraged regular refinement as a team

I lead a team of data engineers to rewrite our legacy systems and expand VictorOps reporting data capabilities

* Reliably delivered critical reporting data in a secure and low latency pipeline utilizing S3, Lambda, and Kinesis

* Built out visibility and alerting utilizing Prometheus/Grafana for our internal tooling

* Built out infrastructure as code utilizing Terraform to enable repeatable pipelining solutions

* Optimized performance of Postgres and MySQL databases and data reliant processes

* Worked within our Scala backend to provide performant and accurate reporting data

* Designed a process for complete deletion of historical VictorOps reporting data to ensure compliance.

* Designed and enforced JSON Schema contracts that improve reporting data ingest reliability from our application data

* Diagrammed and documented architecture to improve our understanding of our data platform

* Regularly mentored and guided engineers in best practices

I worked with data scientists to deliver, optimize, and train machine learning models

* Created and optimized pipelines for our machine learning platforms

* Led architecture for all greenfield Spark EMR applications

* Designed a FastAPI Python back-end to facilitate the utilization of our ML models and responses

* Integrated our ML back-end with our React/Redux front-end applications

* Engineered multi-environment pipeline CI/CD

* Built ML visualizations using plotly

* Generated sample visualizations to allow customers to understand our solutions

* Exported data from non-standard sources in order to quickly iterate on solutions

* Mentored junior developers on best practices and problem solving techniques