Senior Data Engineer

Babylist

6d • Remote

About The Position

The Data team at Babylist powers decision-making across the entire business — from product growth to operations to AI. This is a senior individual contributor role on the Data Engineering team, sitting at the intersection of platform thinking and AI-native tooling. You'll own the architecture and systems that make data engineering itself more scalable — not just the pipelines, but the harnesses and agentic scaffolding that generate, test, and maintain them. You'll work cross-functionally with analysts, data scientists, and product teams to keep Babylist's data infrastructure reliable and ahead of where the business is going.

Requirements

• Experienced building production AI/LLM systems — RAG pipelines, agentic workflows, tool integrations (e.g., MCP servers) that real users depend on, not just prototypes
• Platform-minded — you see repetitive data engineering work as a system design problem and build the scaffolding to automate it
• Deeply fluent in Python and production-grade data engineering, with 7+ years building systems that hold up at scale
• Proficient with Airflow and dbt — you understand data modeling and ETL principles, not just the tooling
• Comfortable in AWS — you've provisioned and managed cloud data resources across EC2, S3, Lambda, and EKS
• Familiar with Snowflake or comparable modern cloud data warehouses
• Able to work cross-functionally with analysts and data scientists — translating their needs into infrastructure that actually serves them
• You naturally reach for AI in your work — at Babylist, every team uses AI daily. You're already using it to move faster and improve your output, and you stay curious about what's coming next.
• You're genuinely excited about what AI can do - not just as a concept, but as something you want to get your hands on. At Babylist, every team uses AI daily, and we're looking for people who lean in.

Responsibilities

• Build and scale data pipelines for ingestion into Snowflake — with a focus on reliability and performance across a $750M+ e-commerce business
• Design and ship the agentic systems that perform data engineering work — pipeline generation, testing, and maintenance as automated systems, not one-off builds
• Develop and maintain ML pipelines that help data scientists operationalize models and integrate them with our data infrastructure
• Implement and improve data monitoring across complex, multi-system user journeys
• Collaborate with Analytics Engineers on data modeling and the reliability of shared data assets
• Partner with product, analyst, and ML teams to deliver end-to-end data solutions — from ingestion to advanced analytics and AI

Benefits

• Company-paid medical, dental, and vision insurance
• Retirement savings plan with company matching and flexible spending accounts
• Generous paid parental leave and PTO
• Winter Wonder Week: the whole company takes a paid week off at the end of the year, whether or not you celebrate anything, so everyone's out at once and comes back refreshed
• Remote work stipend to set up your office
• Perks for physical, mental, and emotional health, parenting, childcare, and financial planning

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed