Senior Analytics Engineer — Product Data Foundation

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

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.