Senior Analytics Engineer

Who We Are

Babylist is the leading registry, e-commerce, and content platform for growing families. More than 9 million people shop with Babylist every year, making it the go-to destination for seamless purchasing, trusted guidance, and expert product recommendations for new parents and the people who love them. What began as a universal registry has grown into a full ecosystem for new parents, including the Babylist Shop, Babylist Health, and a flagship showroom in Los Angeles. Hundreds of brands in baby and beyond partner with Babylist to engage meaningfully with families during one of life’s most important transitions. With over $1 billion in annual GMV, and more than $500 million in 2024 revenue, Babylist is reshaping the $320 billion baby product industry. We’re helping parents feel confident, connected, and cared for at every step. As we build the generational brand in baby, our mission remains simple: to connect growing families with everything they need to thrive.To learn more, visit www.babylist.com.

Our Ways of Working

Babylist thrives as a remote-first company, with HQ team members located across the U.S. and Canada. We meet in person twice a year—once as a company and once by department to strengthen the relationships that power our work. We show up consistently, stay purpose-driven, and achieve results —together, from anywhere.

Our Tech Stack

• Warehouse: Snowflake
• Transformation: dbt
• Workflow Orchestration: Airflow
• BI/Visualization: Sigma
• Scripting & Data Tools: Python, Git, dbt Cloud
• Cloud: AWS

What the Role Is

The Data Team at Babylist powers data-informed decisions across every part of the business. We sit at the intersection of engineering, analytics, and data science, and we’re growing our team with a focus on high-quality, pragmatic solutions that help move the business forward. We’re hiring a Senior Analytics Engineer with deep experience in data modeling and a full-stack mindset. You’ll play a key role in designing and delivering well-structured, reliable data products using our modern data stack. You’ll collaborate across Product, Engineering, and Executive Leadership to build trusted data foundations and models that support the company’s most critical decisions.

We’re looking for someone eager to deepen their craft, build trust through high-quality work, and help shape how we use data to drive impact. You bring a thoughtful approach to balancing long-term quality with near-term value, and you’re motivated by making meaningful contributions that earn influence over time.

Who You Are

• 5+ years experience in analytics or data engineering, with a strong focus on building scalable data models
• Deep fluency in SQL and dimensional modeling (star schema, slowly changing dimensions, surrogate keys, etc.)
• 3+ years experience working in dbt, ideally in a production environment with CI/CD and testing as a well established core principle
• Comfortable working across the full stack: Sigma, dbt, Snowflake, Airflow, Python (or similar tools)
• Strong stakeholder management skills, including experience presenting to executives or C-level leaders
• Pragmatic approach to tradeoffs—can balance long-term maintainability with short-term value
• Enjoys working as part of a collaborative, supportive, and mission-driven team
• Experience with ML data pipelines, Terraform, or DevOps 
• Exposure to entity-centric modeling, data vaults, or alternatives to traditional dimensional models

How You Will Make An Impact

• Own and evolve core data models that drive company-wide reporting, metrics, and analysis
• Build robust, maintainable dbt models that form the foundation of our analytics layer
• Collaborate with cross-functional teams to define and model key business metrics
• Work across our stack (Snowflake, Airflow, dbt, Python, Sigma) to deliver clean and trustworthy data products
• Help define, enforce, and improve standards for documentation, testing, observability, and performance
• Partner with stakeholders—including senior leaders—to understand data needs and ensure solutions align with business goals
• Mentor others in data modeling and best practices

Why You Will Love Working At Babylist

• We invest in the infrastructure you’ll need to be supported and successful: tools, opportunities to connect with colleagues, and a stipend to help you set up your office
• We build products that have a positive impact on millions of people’s lives
• We work at a sustainable pace which means work/life balance is a real thing here
• We believe technology and data can solve hard problems 
• AI plays a meaningful role in how we work, create, and scale—intentionally embedded in our tools, systems, and decision-making to support innovation and real impact
• We believe in exceptional management 
• We offer competitive pay and meaningful opportunities for career advancement
• We have great benefits like company paid medical, dental, and vision and a generous paid parental leave policy
• We care about employee wellbeing with perks for physical, mental and emotional health, parenting, childcare, and financial planning

Babylist takes a market-based approach to pay, and pay may vary depending on your location. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location.

The estimated pay range for this role is CAN $150,500.00 - $188,000.00

In addition, Babylist offers equity, bonus, and benefits, including company paid health, dental and vision insurance, flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies.

Interview Process & Data Use
To support a fair and consistent hiring process, Babylist uses AI to transcribe all interviews. Transcripts are confidential and used solely for evaluation purposes, in accordance with data privacy laws such as CCPA and GDPR. By applying, you acknowledge and consent to this use.

Official Communication
All communication regarding your application will come only from the Babylist Talent Team via an @babylist.com email address. We will never request payment, bank information, or personal financial details. Be cautious of fraudulent outreach via non-company email addresses, messaging platforms (e.g., WhatsApp, Telegram), or unsolicited phone calls. To verify legitimate opportunities, visit our careers page.

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