B
Babylist
Senior Data Engineer
Skills
Data EngineeringE-commerce WebsitesPythonAmazon EC2AWS LambdaSnowflakeData AnalysisMachine LearningAIAWSdbtApache Airflow
2 months ago
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Important information
Contract type:
Permanent
Location:
Ottawa, ON, Canada
Work mode:
Onsite
Published on:
10 September 2026
What they need
- 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
- 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
Benefits
- HAPPIER WEEKENDS – We work to live, not live to work. That means we generally don’t work nights or weekends, and we offer 10 paid holidays throughout the year, in addition to your paid time off.
- PAID TIME OFF THAT WORKS FOR YOU – Life is unpredictable. Use your time off for what you need, whether that’s a vacation, family event or a day to unplug.
- PARENTAL LEAVE – We offer a flexible, 12-week paid parental leave policy.
- FLEXIBLE BENEFITS – Choose from benefits that support your working style, whether that’s remote, in the office or something in between.
- HEALTH & WELLNESS – Wellness benefits include 100% paid coverage for medical, vision and dental for full-time employees.
- BABYLIST STORE DISCOUNT – All full-time employees receive a generous Babylist Store discount.- Platform-minded — you see repetitive data engineering work as a system design problem and build the scaffolding to automate it
- Comfortable in AWS — you’ve provisioned and managed cloud data resources across EC2, S3, Lambda, and EKS
- Experienced building production AI/LLM systems — RAG pipelines, agentic workflows, tool integrations (e.g., MCP servers) that real users depend on, not just prototypes
- Able to work cross-functionally with analysts and data scientists — translating their needs into infrastructure that actually serves them
- Deeply fluent in Python and production-grade data engineering, with 7+ years building systems that hold up at scale
- Familiar with Snowflake or comparable modern cloud data warehouses
- 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
- 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
- Proficient with Airflow and dbt — you understand data modeling and ETL principles, not just the tooling
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