Project Setup

1. Download dbt repo

1. Fork the Repo to your own GitHub account. Be sure to mark it private
   • Screenshots
2. Clone the forked repo to your local machine.
3. Ideally make the repo private so other potential candidates cannot find your work.
   1. If done, grant lordhumunguz (Fei’s GitHub) read access to the repo.

• Replace service_account.json with the content below (click on caret to expand)

2. Export env vars

cd into your dbt project directory and type the following in your command line:

• export DBT_PROFILES_DIR=.
• export OUTPUT_DATASET=masterset_1|2|3|4|5|6 – be sure to check which number you are.

3. Model the data in DBT

• With the blank dbt project, showcase your sql chops, code organization
• Be sure to include testing. BONUS if you can showcase how you go beyond the typical not_null/unique testing. We do extensive testing and the ability to think about testing thoughtfully is very important.

4. Accessing the raw and transformed data

• You will have read-only access granted to your personal gmail account at the wise-weaver-282922 project in BigQuery.
• Raw data is at raw_data_sandbox.acme1_recharge_subscriptions
• Transformed data is at masterset_{{YOUR_OUTPUT_NUMBER}}.{{TABLE_NAME}}

4. Delivery

1. Document any needed documentations within the README.md file.
2. Provide @lordhumunguz read access to this repo.