Tom Waterman, Developer in Amsterdam, Netherlands
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Tom Waterman

Verified Expert  in Engineering

Data Build Tool (dbt) Developer

Location
Amsterdam, Netherlands
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.

Data EngineeringAnalyticsData ScrapingData MiningData AnalyticsPythonPostgreSQLPandasNumPyJupyterGitSQLFlaskApache AirflowRedshift

Portfolio

Miro
Data Build Tool (dbt), Snowflake, Data Analytics, Analytics
Facebook
SQL, Python, Data Analytics, Analytics, Data Science
Poll Everywhere
Apache Airflow, SQL, Python, Amazon RDS, Data Analytics, Analytics

Experience

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

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

Analytics Engineer

2021 - 2023
Miro
  • Drove a cloud data warehouse migration to Snowflake.
  • Implemented and oversaw development for a greenfield data build tool (dbt) project, growing to hundreds of contributors and thousands of models.
  • Implemented key ingestion pipelines for a cloud data warehouse, encompassing dozens of data sources and over three billion daily records.
Technologies: Data Build Tool (dbt), Snowflake, Data Analytics, Analytics

Data Scientist

2018 - 2021
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, Data Analytics, Analytics, Data Science

Data Engineer, Product Analyst

2016 - 2018
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, Amazon RDS, Data Analytics, Analytics

Business Analyst

2014 - 2016
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

Greenfield Airflow Deployment

Deployed a greenfield Airflow project to build the company's first data pipelines.

The Airflow instance managed ETL jobs to ingest data from numerous sources, including the company's internal databases, applications, and 3rd-party data.

Additionally, the instance managed the company's first data transformation pipelines, helping standardize key metrics, including MAUs (monthly active users).

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.

Cloud Data Warehouse Migration

Drove an initiative to migrate the company's data pipelines onto Snowflake, a cloud data warehouse. The project scope included migrating data ingestion pipelines, building key "master data" data sources with dbt, and implementing orchestration and observability with Airflow.

Languages

Python, SQL, R, Snowflake

Frameworks

Flask, Presto

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 Analytics, Data Build Tool (dbt), Amazon RDS, Managed Analytics

Platforms

Amazon Web Services (AWS), Docker, Ubuntu

2010 - 2014

Bachelor's Degree in Mathematics and Statistics

Boston University - Boston, Massachusetts

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