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Salary: USD 185,000 - 195,000 / annual
Good Inside is a parenting education platform founded by Dr. Becky Kennedy and Dr. Erica Belsky that combines technology with expert guidance to help parents raise resilient, confident children. The company has reached millions of users and is expanding its product and reach.
You will own the data foundation behind Good Inside's product, building the models, tracking, and pipelines that reveal how parents discover, adopt, and retain engagement with the platform. This is a full-stack analytics engineering role weighted heavily toward analytics engineering work.
Key responsibilities include:
• Design and maintain production-grade dbt models for product events, engagement metrics, and the member journey from onboarding through retention, ensuring Product teams trust the data.
• Own Amplitude event taxonomy and tracking plans, partnering with product managers and engineers to ensure new features ship with proper instrumentation and consistent definitions across app and web.
• Model the subscription lifecycle (trials, conversions, upgrades, churn, reactivations) and connect it to product behavior, working with Engineering and Finance.
• Implement testing, monitoring, and alerting to catch data quality issues early, improve freshness, and ensure teams have reliable data.
• Answer Product's highest-impact questions directly through funnel and cohort analysis, experiment readouts, and statistical modeling (churn, propensity) when needed, leading with clear recommendations.
• Build semantic layers and dashboards in Omni and Amplitude to enable Product to self-serve on routine questions.
• Partner closely with Product, Engineering, and the Data Analytics team, influencing architecture decisions with downstream data impact and mentoring team members.
You'll sit close to the Product team, serving as a bridge between Product, Engineering, and Data to ensure tracking and metrics are built in from the start rather than patched in later. This role is ideal for someone who thinks like a software engineer, has embedded with product teams at subscription businesses, leverages AI-assisted workflows, and takes pride in clean, maintainable systems.
The role is hybrid based in Manhattan with three days onsite.
**Requirements:**
• 8+ years in analytics engineering, data engineering, or product analytics roles, with at least 2 years supporting a product team
• Deep hands-on dbt experience in production
• Expert SQL and strong Python for modeling, pipelines, and analysis
• Experience with modern data warehouses (Snowflake) and orchestration/ingestion tools (Airflow, Fivetran, or similar)
• Deep experience with event-driven product data and Amplitude (or Mixpanel, Heap), including owning event taxonomy and tracking plans
• Strong understanding of subscription businesses: trial conversion, retention cohorts, LTV, churn, and Stripe or app store billing data
• Track record of analysis that changed product decisions, plus solid grounding in experimentation and statistics
• Experience designing clean, modular, well-tested data models for analytics
• Proficiency with Git and collaborative engineering workflows
• Ability to make sound architectural decisions without heavy oversight, balancing speed with long-term maintainability
• Comfort with AI-assisted development tools to increase velocity while maintaining high accuracy standards
• Clear communicator who leads with recommendations and thrives in fast-moving environments
**Bonus experience:**
• Direct-to-consumer subscription experience, especially with app store and web purchase flows
• Data science experience: churn or propensity modeling, survival analysis, or causal inference
• Pricing, packaging, or paywall experimentation
• Mobile app analytics and attribution
• Familiarity with Segment, Braze, and BI semantic layers (Omni a plus)
• Experience mentoring analysts or teaching stakeholders to self-serve
