Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

Workflow Engine for Kubernetes

Apache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow with low-code

PipelineAI

Build data pipelines, the easy way 🛠️

Docker Apache Airflow

Curated list of resources about Apache Airflow

DataSphereStudio is a one stop data application development& management portal, covering scenarios including data exchange, desensitization/cleansing, analysis/mining, quality measurement, visualization, and task scheduling.

Elyra extends JupyterLab with an AI centric approach.

A series of DAGs/Workflows to help maintain the operation of Airflow

Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.

An end-to-end GoodReads Data Pipeline for Building Data Lake, Data Warehouse and Analytics Platform.

Dynamically generate Apache Airflow DAGs from YAML configuration files

More than 2000+ Data engineer interview questions.

Example end to end data engineering project.

A Data Engineering & Machine Learning Knowledge Hub

🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟𝗘 & 𝗠𝗟𝗢𝗽𝘀 for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

Personal Data Engineering Projects

Optimus is an easy-to-use, reliable, and performant workflow orchestrator for data transformation, data modeling, pipelines, and data quality management.

The User-Community Airflow Helm Chart is the standard way to deploy Apache Airflow on Kubernetes with Helm. Originally created in 2017, it has since helped thousands of companies create production-ready deployments of Airflow on Kubernetes.