Data Build Tool (DBT) Developer in San Francisco, CA, United States

A greenfield Docker-based Airflow deployment used for building out the company's first data pipelines. The Airflow app managed ETL jobs that connected the company's internal services and vendor platforms with their data warehouse.
The app was also responsible for calculating the company's KPIs including daily active users, performing lead-scoring of new users, and monitoring the quality of data ingestion. The data pipelines in the application were used for several mission-critical projects, including A/B testing new pricing models and validating the effects of new feature releases of the company's customer-facing applications.

Built a lead scoring system that automatically ranked all new users based on their propensity to become qualified leads, and then allocated the most qualified leads to the sales team each day for further qualification. The system used signals from data enhancement sites like Clearbit, engagement with marketing content on the company's website, and product usage to help improve the efficiency of our inside sales team and lead nurturing campaigns.

Built data analytics, including data pipelines and statistical significance calculations, for A/B tests of the company's pricing plans and feature releases. Provided recommendations based on that analytics which significantly affected the company's pricing strategy and product roadmap.