Senior Analytics Engineer

goodinside; New York (NY); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Good Inside in Manhattan, NY, is seeking a Senior Analytics Engineer to own the data foundation behind our product. You will design production-grade dbt models for events and engagement, manage Amplitude instrumentation, and keep data fresh and trusted to answer critical product questions.

You will partner closely with Product, Engineering, and the Data Analytics team to translate data into actionable insights, build dashboards, and drive decisions that improve user retention and satisfaction.

Qualifications

• Minimum 8+ years in analytics engineering, data engineering, or product analytics.
• Deep hands-on dbt experience in production.
• Expert SQL and strong Python for modeling, pipelines, and analysis.
• Experience with Snowflake and orchestration tools (Airflow, Fivetran).
• Strong understanding of subscription products and analytics impact.

Responsibilities

• Build the Product Data Foundation with modular dbt models for events, engagement, and user lifecycle.
• Maintain Amplitude event taxonomy and tracking plans; ensure consistent definitions across apps.
• Model subscription data and connect to product behavior with Engineering and Finance.
• Set up testing, monitoring, and alerting to protect data quality.
• Turn data into product decisions with funnel/cohort analysis and experiments.
• Enable self-serve analytics with semantic layers in Omni and Amplitude.
• Collaborate with Product, Engineering, and Data Analytics; mentor teammates.

Skills

SQL

Python

dbt

Amplitude Tracking

Leadership

Experimentation

Tools

Snowflake

Airflow

Fivetran

Git

Job 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.
• Turn Data into Product Decisions Answer Product's highest-impact questions directly: funnel and cohort analysis, experiment readouts, and churn or propensity models when a question calls for it. Lead with a clear recommendation.
• Enable Self-Serve Build the semantic layer and dashboards in Omni and Amplitude so Product can answer routine questions without waiting on Data.
• Partner and Influence Work closely with Product, Engineering, and the Data Analytics team, weigh in on architecture decisions with downstream data impact, and mentor others on the team. Balance competing priorities without lowering the bar.

Your Skills & Experience

• 8+ years in analytics engineering, data engineering, or product analytics roles, with at least 2 supporting a product team
• Deep hands-on dbt experience in production
• Expert SQL and strong Python for modeling, pipelines, and analysis
• Experience with a modern data warehouse (Snowflake) and orchestration and 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
• A track record of analysis that changed what got built, plus solid grounding in experimentation and statistics
• Experience designing clean, modular, well-tested data models for analytics use
• Proficient with Git and collaborative engineering workflows
• Make sound architectural decisions without heavy oversight, balancing speed with long-term maintainability
• Embrace AI-assisted development tools to increase velocity while keeping a high bar for accuracy
• Clear communicator who leads with a recommendation and thrives in fast-moving environments

Bonus Points

• Direct-to-consumer subscription experience, especially with app store and web purchase flows and the gaps between them
• 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)
• Ex