Teams at Phantom (phantom.com)

Build and scale Phantom’s data infrastructure for analytics, experimentation, and decision-making. Responsibilities include designing high-volume data architecture, leading data quality and observability initiatives, developing scalable data models, building A/B testing infrastructure, partnering cross-functionally, and mentoring teams. The role requires expertise in Snowflake, dbt, SQL, Python, data architecture, data modeling, and experimentation systems, with blockchain experience preferred.

Manage and scale AWS EKS Kubernetes clusters, automate infrastructure with Terraform or Pulumi, optimize system performance, maintain blockchain nodes, scale databases handling terabytes of data, and improve reliability through monitoring and observability. Collaborate with backend and product teams to support feature development and platform scalability.

Lead the technical strategy, architecture, and delivery of growth and engagement machine learning systems. Build production ML pipelines, real-time decisioning, recommendation engines, semantic search, lifecycle models, and experimentation frameworks. Partner with Product, Data Science, and Marketing to improve acquisition, retention, lifetime value, and engagement. Mentor senior engineers while establishing best practices for monitoring, feature stores, reproducible training, and data governance.