Senior Analytics Engineer
Owns the product data foundation at a parenting-guidance subscription company: builds production dbt models, Amplitude tracking plans, and subscription lifecycle pipelines, and turns data into funnel, cohort, and experiment analyses for Product. Core stack: dbt, SQL/Python, Snowflake, Airflow/Fivetran, Amplitude. Hybrid, 3 days onsite in Manhattan.
- Compensation
- $185K–$195K / yr
- Location
- New York, NY (Hybrid Manhattan)
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Data analytics
- Posted
Skills
Must have
- 8+ years in analytics engineering, data engineering, or product analytics, 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 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, Stripe or app store billing data
- Track record of analysis that changed what got built, plus grounding in experimentation and statistics
- Experience designing clean, modular, well-tested data models
- Proficient with Git and collaborative engineering workflows
- Sound architectural decisions without heavy oversight, balancing speed with maintainability
- Embrace AI-assisted development tools to increase velocity
- Clear communicator who leads with a recommendation, thrives in fast-moving environments
Nice to have
- Direct-to-consumer subscription experience with app store and web purchase flows
- Data science experience: churn/propensity modeling, survival analysis, 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
Full description
Who We Are
Good Inside is redefining parenting - not as something that should “just come naturally,” but as a skill to learn and practice. Founded by Dr. Becky Kennedy and Dr. Erica Belsky, we combine sturdy leadership with innovative technology to give parents personalized guidance, AI-powered support, and a global community.
Our mission: help parents raise resilient, confident kids in a changing world. We’ve already reached millions, and we’re just getting started. We’re refining our product and expanding our reach to empower even more families.
We’re looking for bold, high-ownership problem-solvers who want to build something new, tackle big challenges, and be at the forefront of change.
The Opportunity
Good Inside is seeking a Senior Analytics Engineer to own the data foundation behind our product. You'll build the models, tracking, and pipelines that tell us how parents discover, adopt, and keep coming back to Good Inside, and you'll use them to answer Product's most important questions yourself.
This is a full stack role, weighted toward analytics engineering. You'll design production-grade dbt models for product events and subscription data, own our Amplitude instrumentation and tracking plans, and keep data fresh, tested, and trusted. Because you'll sit close to Product, you'll also turn that foundation into analysis, experiment readouts, and recommendations, using statistical methods when a question needs more than a dashboard.
You'll be the bridge between Product, Engineering, and the Data team, so tracking and metrics are built in from the start rather than patched in after launch. This role is ideal for someone who thinks like a software engineer, has embedded with product teams at a subscription business, leverages AI-assisted workflows to move faster, and takes pride in clean systems that change what gets built.
This is a hybrid role based in Manhattan with three days onsite.
What You’ll Own
- Build the Product Data Foundation Design and maintain clean, modular dbt models for product events, engagement, and the member journey, from onboarding and activation through retention. Create well-documented transformations so Product trusts the numbers.
- Build Tracking and Instrumentation Maintain our Amplitude event taxonomy and tracking plans. Partner with PMs and engineers so new features ship with the right events, and keep definitions consistent across app and web.
- Model Subscription Data Model the subscription lifecycle (trials, conversions, upgrades, churn, reactivations) and connect it to product behavior, aligned with Engineering and Finance.
- Protect Data Quality Set up testing, monitoring, and alerting. Catch inconsistencies early, improve freshness, and make sure teams aren’t waiting on or questioning the data.