Senior Data Engineer

Babylist is the leading platform for expecting and new families. More than 10 million people shop with Babylist every year, making it the go-to destination for seamless purchasing, guidance, and expert recommendations. As a modern, AI-forward tech company, Babylist has expanded from a universal registry into a full ecosystem — the Babylist Shop, Babylist Health, Babylist Money, NYC and LA showrooms, branded content, and more — generating $750M in revenue in 2025. Building the generational brand in baby, Babylist is reshaping the $235B kids and baby market and helping parents feel confident, connected, and cared for at every step.

Babylist is remote-first with team members across the U.S. and Canada who move fast, think smart, and use AI as part of how they work every day — not as an experiment, as an expectation. We come together twice a year to build the relationships behind the work, and we hire people who are genuinely excited about what's possible and prove it through how they show up.

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.

• 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.

• 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\

• You're building the meta-layer — not just pipelines, but the systems that build pipelines; it's a rare scope for a data engineering role
• The data infrastructure is solid; you're extending and automating something that works, not inheriting a mess
• AI is core to the mandate here, not a future aspiration — agentic data engineering is a real part of the roadmap, not a stretch goal
• You'll have direct influence on how a 9M+ user platform scales its data systems through a pre-IPO growth moment.

• We work with focus and intention, then step away to recharge
• We believe in exceptional management and invest in tools and opportunities to connect with colleagues
• We build products that positively impact millions of people's lives
• AI is intentionally embedded in how we work, create, and scale—supporting innovation and impact

• Competitive pay and meaningful opportunities for career advancement
• We believe technology and data can solve hard problems
• We're committed to career progression and performance-based advancement

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Interview Integrity. AI is part of how we work at Babylist — we expect you to use it too. Your application and interviews should still reflect you and your own thinking. We'll tell you when AI is encouraged. Misrepresentation at any stage may result in removal from consideration for this and future roles.

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