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Staff DevOps Engineer with expertise in microservice design, automating deployments, monitoring services, and supporting machine learning.
> DevOps
- Participate in DevOps support of 200 engineers who deploy to production 1000 times per week across hundreds of services [CICD, troubleshooting]; core maintainer of an in-house Terraform deploy tool (Golang).
- Administrator of Kubernetes clusters. Designed multi-cluster strategy, governance, and topology. Automated deployment of core Operators and alarms in each cluster [ArgoCD, LB, DNS, Kube State, Secrets, OPA].
- Administrator of Kafka clusters that supports 100k writes/s. Lead architect of a microservice strategy of Kafka Connect to host 250 connectors, each in isolated deployments (AWS ECS, Java).
- Improved velocity of machine learning engineers by using Helm charts and Karpenter to spin up/down GPU nodes as needed to serve models. Docker mirror was added to reduce image pull time; cut model deployment time by 70%.
> Backend Engineering
- Wrote Kafka producers and consumers to handle asynchronous communication for critical high throughput; Superbowl Ad that resulted in 1.2M signups in 2 minutes.
- Wrote Feature Store API to serve S3 URIs to machine learning model training jobs; given parameters of dataset, version, and timestamps (Golang).
- Wrote ETL microservice that tails Graph Database CDC and normalizes JSON; 15k records/s (Golang, K8s Deployment).
> Data Engineering
- Built highly scalable social media scraping apps that accounted for sessions and rate limiting (Kotlin, K8s Deployment).
- Created daily batch job to clean text from social media posts and comments. A scoring model picked up the clean data to vectorize and predict (sklearn, spaCy, K8s CronJob).
M.S. Data Science, Data Engineering
