Senior Analytics Engineer

Good Inside•New York, NY

3d•$185,000 - $195,000•Hybrid

About The Position

Good Inside is seeking a Senior Analytics Engineer to own the data foundation behind its product. This full-stack role is weighted toward analytics engineering and focuses on building the models, tracking, and pipelines that help the company understand how parents discover, adopt, and continue using Good Inside. The role also directly answers Product’s important questions through analysis, experiment readouts, and recommendations. The Senior Analytics Engineer will design production-grade dbt models for product events and subscription data, own Amplitude instrumentation and tracking plans, and ensure data is fresh, tested, and trusted. Working closely with Product, Engineering, and Data Analytics, this person will help ensure tracking and metrics are incorporated into new features from the start. The position is hybrid and based in Manhattan, with three days onsite.

Requirements

At least 8 years of experience in analytics engineering, data engineering, or product analytics, including at least 2 years supporting a product team.
Deep hands-on experience with dbt in production.
Expert SQL skills and strong Python skills for modeling, pipelines, and analysis.
Experience with a modern data warehouse such as Snowflake and orchestration and ingestion tools such as Airflow and Fivetran, or similar tools.
Deep experience with event-driven product data and Amplitude or comparable tools such as Mixpanel or Heap, including ownership of event taxonomies and tracking plans.
Strong understanding of subscription businesses, including trial conversion, retention cohorts, lifetime value, churn, and Stripe or app store billing data.
A track record of analysis that influenced what was built, with a 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 while balancing speed and long-term maintainability.
Willingness to use AI-assisted development tools to increase velocity while maintaining a high bar for accuracy.
Clear communication skills, a recommendation-oriented approach, and ability to thrive in a fast-moving environment.

Nice To Haves

Direct-to-consumer subscription experience, especially with app store and web purchase flows and the differences between them.
Data science experience, including churn or propensity modeling, survival analysis, or causal inference.
Experience with pricing, packaging, or paywall experimentation.
Mobile app analytics and attribution experience.
Familiarity with Segment, Braze, and BI semantic layers; Omni experience is a plus.
Experience mentoring analysts or teaching stakeholders to self-serve.

Responsibilities

Design and maintain clean, modular, documented dbt models for product events, engagement, and the member journey from onboarding and activation through retention.
Maintain Amplitude event taxonomy and tracking plans, partnering with product managers and engineers to ensure new features have appropriate events and consistent app and web definitions.
Model subscription lifecycle events—including trials, conversions, upgrades, churn, and reactivations—and connect them to product behavior in alignment with Engineering and Finance.
Establish data testing, monitoring, and alerting; identify inconsistencies, improve data freshness, and ensure teams can rely on the data.
Conduct funnel and cohort analyses, experiment readouts, and churn or propensity modeling as needed; communicate clear recommendations to inform product decisions.
Build the semantic layer and dashboards in Omni and Amplitude to enable Product self-service for routine questions.
Collaborate with Product, Engineering, and Data Analytics; advise on architecture decisions with downstream data impact; mentor others; and balance competing priorities while maintaining quality.