Make stream processing easier! Easy-to-use streaming application development framework and operation platform.

Implementing best practices for PySpark ETL jobs and applications.

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

Build data pipelines, the easy way 🛠️

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

A simplified, lightweight ETL Framework based on Apache Spark

Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.

This repository will help you to learn about databricks concept with the help of examples. It will include all the important topics which we need in our real life experience as a data engineer. We will be using pyspark & sparksql for the development. At the end of the course we also cover few case studies.

Azure Data Factory Hands On Lab - Step by Step - A Comprehensive Azure Data Factory and Mapping Data Flow step by step tutorial

An end-to-end data engineering pipeline that orchestrates data ingestion, processing, and storage using Apache Airflow, Python, Apache Kafka, Apache Zookeeper, Apache Spark, and Cassandra. All components are containerized with Docker for easy deployment and scalability.

an app engine for your business. Seamlessly implement business logic with a powerful API. Out of the box CMS, blog, forum and email functionality. Developer friendly & easily extendable for your next SaaS/XaaS project. Built with Rails 6, Devise, Sidekiq & PostgreSQL

Download DIG to run on your laptop or server.

A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton

Regular practice on Data Science, Machien Learning, Deep Learning, Solving ML Project problem, Analytical Issue. Regular boost up my knowledge. The goal is to help learner with learning resource on Data Science filed.

The goal of this project is to track the expenses of Uber Rides and Uber Eats through data Engineering processes using technologies such as Apache Airflow, AWS Redshift and Power BI.

Simplified ETL process in Hadoop using Apache Spark. Has complete ETL pipeline for datalake. SparkSession extensions, DataFrame validation, Column extensions, SQL functions, and DataFrame transformations

A Clojure high performance data processing system

A simple Spark-powered ETL framework that just works 🍺

This is a template you can use for your next data engineering portfolio project.

Data Engineer with Python lecture notes from #datacamp.