Data Engineer
Own data and analytics end-to-end: architect internal systems, build metrics/dashboards, and translate customer and product signals into structured inputs for AI agents.
Builds and maintains scalable data processing pipelines and backend systems for a data curation platform that optimizes training data for ML models. Partners with researchers to integrate research capabilities, ensuring reliability and security for customer data.
Own data and analytics end-to-end: architect internal systems, build metrics/dashboards, and translate customer and product signals into structured inputs for AI agents.
Builds and scales internal data platform by designing data models, pipelines, and analytics infrastructure to transform raw product/business data into reliable datasets for company-wide decision-making. Partners with stakeholders across Product, Engineering, Finance, Marketing, and Sales.
Builds and operates petabyte-scale data platform infrastructure using Kafka, Spark, Flink, and Trino to power real-time ML pipelines and analytics. Requires expertise in distributed systems, stream processing, and systems languages like Rust, Go, or Scala.
Architects and builds massive-scale data infrastructure for web crawling, embedding model training, and real-time search, handling hundreds of petabytes. Requires expertise in lakehouse architectures, distributed processing pipelines, and streaming systems like Kafka and Flink.
Designs and owns mission-critical data pipelines to enable decision-making across data science, growth, sales, marketing, and product teams. Requires 5+ years experience with scalable pipelines (preferably Airflow), Python, and advanced SQL.