Jake Thomas, Developer in 01915, United States
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Jake Thomas

Verified Expert  in Engineering

Data Engineer and Developer

01915, United States
Toptal Member Since
February 8, 2022

Jake is a data engineer experienced in public companies, mid-size private companies, and startups. His past accomplishments include migrating data warehouses to Snowflake, building frameworks to ingest data from hundreds of third-party sources, leveraging DBT tame data modeling, lineage, and documentation, leading data quality and alerting efforts, and teaching online Snowflake courses with Pearson and O'Reilly. Jake is passionate about scaling data systems that empower business decision-making.


6 River Systems
Python, Go, SQL, Google Cloud Platform (GCP), CircleCI, Data Build Tool (dbt)...
Python, SQL, Snowflake, Amazon Web Services (AWS), Data Build Tool (dbt)...
Apache Airflow, Python, Redshift, Docker




Preferred Environment


The most amazing...

...feeling I've achieved in my job is helping people grow in their careers and become better engineers.

Work Experience

Lead Data Platform Engineer

2021 - PRESENT
6 River Systems
  • Created PostgreSQL to BigQuery pipelines across thousands of PG databases.
  • Migrated the in-house data modeling toolsets to DBT, drastically improving data model documentation, lineage, and dependency management.
  • Built, deployed, and maintained streaming event pipelines across thousands of fulfillment robots.
  • Developed and maintained a customer-facing data API to serve data to partners.
Technologies: Python, Go, SQL, Google Cloud Platform (GCP), CircleCI, Data Build Tool (dbt), GitOps, Terraform, Atlantis, BigQuery

Lead Data Engineer

2018 - 2021
  • Migrated a data warehouse from BigQuery to Snowflake.
  • Built a framework to integrate hundreds of third-party sources with Snowflake.
  • Deployed and managed an autoscaling instance of Snowplow Analytics event streaming pipelines. The system processed 12k-15k messages per second continuously.
  • Moved a legacy modeling framework to DBT to make data modeling sustainable and transferable.
  • Wrote Terraform code to deploy all pieces of the analytical infrastructure.
  • Deployed Airflow for DAG scheduling and dependency management.
Technologies: Python, SQL, Snowflake, Amazon Web Services (AWS), Data Build Tool (dbt), Data Warehousing, Data Warehouse Design, Apache Kafka, Apache Airflow, Streaming

Data Engineer

2016 - 2018
  • Set up and maintained a Redshift-based data warehouse.
  • Created data pipelines from various PostgreSQL and Mongo databases to Redshift.
  • Installed and maintained an auto-scaling BI platform.
  • Developed and maintained Snowplow Analytics to collect and warehousing streaming event data.
  • Assembled and maintained Kafka for log and event centralization.
  • Automated AdWords and a traffic acquisition platform.
  • Created pipelines for customer-facing route metrics.
  • Became a certified EnterpriseDB PostgreSQL administrator.
Technologies: Apache Airflow, Python, Redshift, Docker

One Billion Events Per Day with Snowplow and Snowflake

At CarGurus, I led the implementation of an auto-scaling event system that processes over a billion events per day using AWS and Snowflake.

The system collects and stores many petabytes of validated and warehoused data within minutes.

Building a Modern Data Platform with Snowflake

Snowflake is a modern data warehouse that is built for cloud-scale workloads.

I planned, created, and delivered numerous Data Warehousing courses for Pearson on O'Reilly Learning's platform. The introductory course is a three-hour lesson covering getting started using Snowflake from scratch.


Three Reasons Why Your Company Should Own Its Data

Periodically, I guest-post on well-known technical blogs. This post is a collaboration between Snowplow Analytics and my side business and discusses the importance of owning your own data pipelines and storage.


Python, SQL, Snowflake, Go


Terraform, BigQuery, Apache Airflow, Snowplow Analytics, CircleCI


Google Cloud Platform (GCP), Amazon Web Services (AWS), Apache Kafka, Docker, MacOS


Data Build Tool (dbt), Atlantis, Data Warehousing, Streaming, Amazon Kinesis, Data Warehouse Design, AWS DevOps, Web Security, Cloud Security, GitOps





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