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Babylist is seeking a Senior Data Engineer to own the architecture and systems that make data engineering itself more scalable. This is a senior individual contributor role at the intersection of platform thinking and AI-native tooling. You'll work on the meta-layer—not just building pipelines, but designing the agentic systems that generate, test, and maintain them automatically.
You'll be responsible for building and scaling data pipelines for ingestion into Snowflake, supporting a $750M+ e-commerce business serving 10M+ users. Key responsibilities include designing agentic systems that perform data engineering work as automated systems rather than one-off builds, developing and maintaining ML pipelines for data scientists, implementing data monitoring across complex user journeys, and collaborating with analytics engineers on data modeling and reliability.
You'll partner cross-functionally with analysts, data scientists, and product teams to deliver end-to-end data solutions—from ingestion to advanced analytics and AI. The data infrastructure is already solid; you're extending and automating something that works, not inheriting a mess.
Required experience: 7+ years building production systems at scale, deep fluency in Python and production-grade data engineering, proficiency with Airflow and dbt, comfort with AWS (EC2, S3, Lambda, EKS), and familiarity with Snowflake or comparable cloud data warehouses. You should have hands-on experience building production AI/LLM systems—RAG pipelines, agentic workflows, tool integrations (e.g., MCP servers)—and a platform-minded approach to solving repetitive engineering work through system design.
Babyllist is remote-first with team members across the U.S. and Canada. The company is pre-IPO, AI-forward, and uses AI as a core part of daily work. You'll have direct influence on how a 9M+ user platform scales its data systems during a critical growth moment.
