dbt Project Setup & Transform Layer for Analytics

Design and implement a production ETL pipeline for your data ingestion use case. Includes source connectors, transformation logic, scheduling, error handling, and monitoring alerts.

Design and implement a dbt project with staging, intermediate, and mart layers. Includes documentation, tests, and CI/CD integration. Covers up to 10 source tables and 20 models.

Write, review, or optimize 10 complex SQL queries for your analytics use case. Includes execution plan analysis, index recommendations, and documented query explanations. Supports PostgreSQL, BigQuery, Snowflake, Redshift.