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For Data Engineers

This is the path for engineers who need programmatic access: SnowSQL, dbt, and a local development workflow. If you only need to read curated data in the browser, use For Researchers & Analysts instead.

Prerequisites

  • A Natera email address (your_name@natera.com)
  • GitLab access to the eng/cgdb group on gitlab.natera.com
  • AWS CLI configured with the appropriate profiles (cgdb-sbx, cgdb-qa, cgdb-prod)

Step 1: Get provisioned in Snowflake

An admin adds your user to the ndp-account-request repo under accounts/rwd/{env}/teams/rwd/users.json. Once the MR merges, Terraform creates your Snowflake user and provisions the Okta SSO tile. See How to Grant Access for the full workflow.

Step 2: Set up authentication for CLI access

Programmatic Access Tokens (PATs) are the simplest way to authenticate SnowSQL — no key generation or admin involvement. In Snowsight: your name → Settings → Authentication → Programmatic Access Tokens → Generate. Copy the token (you won’t see it again) and add it to ~/.snowsql/config.

Step 3: Install and configure SnowSQL

bash
brew install --cask snowflake-snowsql

Add a connection profile per environment to ~/.snowsql/config:

~/.snowsql/config
[connections.rwd_dev]accountname = WA16250-NATERA_RWD_DEVELOPMENTusername = YOUR_EMAIL@NATERA.COMpassword = <your-dev-PAT>rolename = RWD_DATA_ENGINEER_ROLEdbname = CLINICOGENOMICS

Always pass -c (connection), -w (warehouse — required), and --noup (suppress upgrade prompts):

bash
snowsql -c rwd_dev -w RWD_DEVELOPMENT_QUERY_INTERACTIVE_WH --noup \  -q "SELECT COUNT(*) FROM CLINICOGENOMICS.LIMS_PUB.CASEFILE_FILTERED;"

Step 4: Install and configure dbt

bash
uv tool install dbt-core --with dbt-snowflake --python 3.12

Configure ~/.dbt/profiles.yml with dev, qa, and prod targets, then test the connection:

bash
cd snowflake/dbt && dbt debug --target dev

Step 5: Development workflow

  1. Clone the cgdb repo from GitLab.
  2. Create a worktree for your feature branch.
  3. Make changes to dbt models in snowflake/dbt/.
  4. Test locally against dev.
  5. Create a Merge Request, get review, and merge to master.
  6. CI/CD deploys to environments based on maturity tags.
bash
git worktree add ../cgdb-CGDB-XXXX -b CGDB-XXXX-description origin/mastercd snowflake/dbt && dbt run --select my_model --target dev

MCP connections (Claude Code / Cursor)

If you use Claude Code or Cursor, Snowflake MCP servers can be configured in ~/.claude/mcp.json. Default to the dev MCP server for all development; use preprod/prod only when explicitly targeting those environments.