Agent skill · data analytics · aradotso
zomato-ai-data-engineering-pipeline
End-to-end batch data pipeline with Snowflake, dbt, Airflow, and OpenAI for food delivery analytics
Why this skill is useful
Adds a complete executable data engineering pipeline with specific commands for Snowflake, dbt, and Airflow that the AI wouldn't generate on its own.
What it needs
Requires apache-airflow, aws-cli, dbt, snowflake-cli installed locally. Requires aws, snowflake account access. About 8k tokens when loaded. Last updated 2026-08-05. 5 stars on the source repository.
What this skill does
zomato-ai-data-engineering-pipeline Skill by ara.so — Data Skills collection. Complete batch data engineering pipeline that processes food delivery data through a medallion architecture (Bronze → Silver → Gold) using Amazon S3, Snowflake, dbt, Airflow orchestration, and OpenAI-powered AI capabilities (LLM enrichment, RAG, text-to-SQL). Project Overview Pipeline Flow: Architecture Layers: Bronze (RAW): Direct COPY INTO from S3 via storage integration Silver (STAGING): dbt views for cleaning, typing, renaming Gold (MARTS): Dimensions, incremental facts (MERGE), business aggregates, SCD2 snapshots AI: LLM enrichment, RAG chat, text-to-SQL queries Data Scale: 10M orders 23M order items 300K text reviews 7 source tables (restaurants, users, food, menu, orders, orderitems, reviews) Installation & Setup Prerequisites AWS S3 Setup Snowflake Setup dbt Configuration Airflow Setup Key dbt Models Staging (Silver Layer) Marts (Gold Layer) dbt Testing Airflow DAG AI Layer LLM Enrichment RAG Chat `python ai/ragchat.py import os import streamlit as st from openai import OpenAI import snowflake.connector import numpy as np OPENAIAPIKEY = os.getenv('OPENAIAPIKEY') client = OpenAI(apikey=OPENAIAPIKEY) def getsnowflakeconnection(): return snowflake.connector.connect( acco
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/zomato-ai-data-engineering-pipeline