About the Role
You'll own the platform that supports over 1 petabyte of intelligence products, including batch processing, real-time, and 24/7 API requirements. You'll build the next generation of foundational AI architecture for blockchain intelligence infrastructure and drive a 10x improvement in the speed of getting new intelligence models and data products to customers. You'll lead and hire for two sub-teams spanning data infrastructure through product-facing delivery, raising the bar on technical quality and AI fluency. As a player-coach, you'll stay close to the technical work, reviewing architecture, debugging pipelines, and making system design decisions, while also setting team strategy and making sound bets on architecture, tooling, and platform investments. You'll build platforms that accelerate the data science team's work, making it seamless and fast for data scientists to test and deliver intelligence data products.
Requirements
- 8+ years of hands-on data/engineering experience with 4+ years of direct people management
- Experience as a player-coach reviewing architecture, debugging pipelines, and making system design decisions while setting team strategy
- Must have owned production systems at scale: customer-facing data products, APIs, or decisioning engines - not analytics or BI systems
- Strong Python and SQL; experience with BigQuery, Airflow, data lake architecture, serving layers
- Active daily user of AI tools to accelerate development and challenge assumptions
- Good judgment for making decisions on technological bets and investments
Responsibilities
- Own the platform that supports 1+ petabyte of intelligence products including batch processing, real-time, 24/7 API requirements
- Build the next-generation of foundational AI architecture for blockchain intelligence infrastructure
- Drive 10x improvement in the speed and overhead of getting new intelligence models and data products to customers
- Lead and hire for two sub-teams spanning from data infrastructure through product-facing delivery
- Set the technical direction for production systems, making sound bets on architecture, tooling, and platform investments
- Build platforms that accelerate data science team work