Agent skill · data analytics · aradotso
datatalks-data-engineering-zoomcamp
Free 9-week data engineering course covering Docker, Terraform, Kestra, BigQuery, dbt, Spark, and Kafka with hands-on projects
Why this skill is useful
Provides executable scripts for Docker and Terraform setups that enhance data engineering workflows.
What it needs
Requires docker, terraform installed locally. Requires google-cloud-platform account access. About 8k tokens when loaded. Last updated 2026-08-05. 5 stars on the source repository.
What this skill does
DataTalks Data Engineering Zoomcamp Skill by ara.so — Data Skills collection. Overview The Data Engineering Zoomcamp is a comprehensive 9-week free course covering production-ready data pipeline development. It includes hands-on modules on containerization (Docker), infrastructure as code (Terraform), workflow orchestration (Kestra), data warehousing (BigQuery), analytics engineering (dbt), data platforms (Bruin), batch processing (Spark), and streaming (Kafka). The course operates in cohorts (next starts January 2026) but all materials are available for self-paced learning. Prerequisites Basic coding experience SQL familiarity Python knowledge (helpful but not required) Git installed Docker Desktop or Docker Engine Google Cloud Platform (GCP) account (free tier) Course Structure Module 1: Docker & Terraform Set up containerized PostgreSQL database: Docker Compose for entire stack: Terraform GCP setup: Module 2: Workflow Orchestration (Kestra) Example Kestra workflow for data ingestion: Python data ingestion script: Module 3: Data Warehouse (BigQuery) Create partitioned and clustered table: Load data from GCS to BigQuery: Module 4: Analytics Engineering (dbt) Project structure: dbtproject.yml: profiles.yml: Staging model (models/staging/stgyellowtripdata.sql): Core model (models/core/facttrips.sql): Macro (macros/getpaymenttypedescription.sql): Schema and tests (models/staging/schema.yml): dbt commands: Module 6: Batch Processing (Spark) PySpark setup: PySpark script for data processing: Spark with Google Cloud Storage: Module 7: Streaming (Kafka) Docker Compose for Kafka: `yaml docker-compose-kafka.yml version: '3.6' services: zookeeper: image: confluentinc/cp-zookeeper:7.2.0 hostname: zookeeper containername: zookeeper ports: "2181:2181" environment: ZOOKEEPERCLIENTPORT: 2181 ZOOKEEPERTICKTIME: 2000 broker: image: confluentinc/cp-kafka:7.2.0 hostname: broker containername: broker dependson: zookeeper ports: "9092:9092" "9101:9101" environment: KAFKABROKERID: 1 KAF …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/datatalks-data-engineering-zoomcamp