Data Engineer

About The Role

We are seeking a highly skilled Senior Data Engineer to join Babylist’s Data team, a critical function that drives strategic decision-making across the entire organization. This role sits at the intersection of platform architecture and AI-native tooling, focusing on building scalable, reliable, and intelligent data infrastructure. You will be responsible for designing and owning the architecture that supports data pipelines, harnesses, and agentic systems that generate, test, and maintain data workflows. Collaborating closely with analysts, data scientists, and product teams, you will ensure that Babylist’s data infrastructure remains robust and adaptive to the company’s rapid growth and technological advancements.

Qualifications

• Extensive experience in building production-grade AI and LLM systems, including retrieval-augmented generation (RAG) pipelines, agentic workflows, and tool integrations such as MCP servers.
• A platform-oriented mindset, viewing repetitive data engineering tasks as system design challenges that can be automated and optimized.
• Deep proficiency in Python and experience developing scalable data systems with at least 7+ years of relevant experience.
• Familiarity with Airflow, dbt, and core data modeling principles.
• Hands-on experience managing cloud resources on AWS, including EC2, S3, Lambda, and EKS.
• Knowledge of Snowflake or comparable cloud data warehouses.
• Strong communication skills for working effectively with cross-functional teams, translating analytical and scientific needs into reliable infrastructure.
• A genuine enthusiasm for AI and its potential to transform data engineering and business operations.

Responsibilities

• Building and scaling data pipelines to support Babylist’s e-commerce platform, focusing on performance and reliability across a $750 million+ business.
• Designing agentic systems that automate data engineering tasks such as pipeline generation, testing, and maintenance, transforming these processes into scalable, automated systems.
• Developing and maintaining machine learning pipelines that enable data scientists to operationalize models and seamlessly integrate them into the broader data infrastructure.
• Implementing comprehensive data monitoring across complex user journeys and multiple systems to ensure data quality and integrity.
• Collaborating with analytics engineers on data modeling and shared asset reliability.
• Partnering with product, analytics, and machine learning teams to deliver end-to-end data solutions—from ingestion to advanced analytics and AI-driven insights—helping to shape the future of Babylist’s data ecosystem.