Tom Waterman, Developer in San Francisco, CA, United States

Tom Waterman

Data Build Tool (dbt) Developer

Location
San Francisco, CA, United States
Toptal Member Since
June 24, 2020

Tom is an experienced data modeler with a decade of experience in the technology sector. He's worked across the data stack in various roles, including data scientist, analytics engineer, and data engineer. His professional experience includes data roles at Facebook and Miro, where he led data warehousing, data modeling, and data platform initiatives.

Tom is available for hire
Hire Tom

Portfolio

Facebook
SQL, Python
Poll Everywhere
Apache Airflow, SQL, Python
Cartesian Consulting
SQL, Python

Experience

Python - 5 yearsSQL - 5 yearsGit - 5 yearsData Science - 5 yearsDocker - 3 yearsRedshift - 3 yearsApache Airflow - 3 yearsData Build Tool (dbt) - 2 years

Location

San Francisco, CA, United States

Availability

Part-time

Preferred Environment

Docker, SQL, Apache Airflow, Python, Data Build Tool (dbt), Snowflake

The most amazing...

...project I've led was a greenfield dbt and Snowflake migration for a hyper-growth SaaS company, which quickly became the foundation of data for the business.

Work Experience

2018 - PRESENT

Data Scientist

Facebook
  • Built and managed data infrastructure for a program's in-house CRM platform. Data infrastructure was used for sourcing new leads, monitoring program efficiency, and integrating data sources.
  • Managed analytics for a new, experimental product developed for small businesses, including targeting criteria, feature-flags used during release, and developing insights about product adoption.
  • Built and maintained lead-scoring models for an on-platform campaign that drove a 30% improvement in cost per campaign objective.
Technologies: SQL, Python
2016 - 2018

Data Engineer, Product Analyst

Poll Everywhere
  • Implemented Airflow and constructed the first data pipelines for the company.
  • Managed the building and design of a data warehouse, including integrating data sources.
  • Built a lead scoring system that automatically funneled leads to the sales team. The system included data enrichment, scoring, and result tracking.
Technologies: Apache Airflow, SQL, Python
2014 - 2016

Business Analyst

Cartesian Consulting
  • Built data pipelines and a scoring system to measure and track the prevalence of account sharing for a video streaming service.
  • Created revenue and operations tracking dashboards for a sales channel of a US wireless carrier.
  • Developed cost-allocation models to assess the profitability of individual enterprise customers for a US communications service provider.
Technologies: SQL, Python

Experience

Greenfield Airflow Deployment

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.

Lead Scoring and Recommendation System

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.

A/B Testing for Pricing Changes and New Feature Releases

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.

Skills

Languages

Python, SQL, R, Snowflake

Frameworks

Flask, Presto DB

Libraries/APIs

Pandas, NumPy, Flask-RESTful

Tools

Amazon Athena, Apache Airflow, Docker Compose, Jupyter, Git

Paradigms

Data Science, Database Design

Storage

PostgreSQL, Redshift, MySQL, Database Architecture, MongoDB

Other

Data Engineering, Analytics, Dashboard Design, Data Scraping, Data Mining, Modeling, Data Build Tool (dbt)

Platforms

Amazon Web Services (AWS), Docker, Ubuntu

Education

2010 - 2014

Bachelor's Degree in Mathematics and Statistics

Boston University - Boston, Massachusetts