#Data-engineer
Showing 21 of 21 repositories tagged #data-engineer, ranked by stars
The Data Engineering Cookbook
The best place to learn data engineering. Built and maintained by the data engineering community.
Best Data Science, Data Analytics, AI, and SDE roadmaps. This repository is continually updated based on the top job postings on LinkedIn and Indeed in the data science and AI domain.
One framework to develop, deploy and operate data workflows with Python and SQL.
:sunglasses: A curated list of awesome DataOps tools
Content for architecting a data science platform for products using Luigi, Spark & Flask.
This is a repository to demonstrate my details, skills, projects and to keep track of my progression in Data Analytics and Data Science topics.
Data Engineering Project with Hadoop HDFS and Kafka
The Data Engineering Book - หนังสือวิศวกรรมข้อมูล ของคนไทย เพื่อคนไทย
🟣 Data Engineer interview questions and answers to help you prepare for your next machine learning and data science interview in 2026.
Road to Azure Data Engineer Part-I: DP-200 - Implementing an Azure Data Solution
DE or DIE meetup made by data engineers for data engineers. Currently in Russian only.
170+ curated resources every Databricks Data Engineer should bookmark - tools, courses, creators, labs, and communities
Data Engineering Digest
Road to Azure Data Engineer Part-II: DP-201 - Designing an Azure Data Solution
Google Cloud Platform Professional Data Engineer Certification resources ☁️☁️☁️
💡 Think Like An Engineer is a roadmap for engineering leadership, a toolkit for growth hacking through engineering, and a manifesto for productivity enhancement
Complete data engineering roadmap with technologies, certifications (AWS, GCP, Azure, Snowflake, Databricks), and learning resources.
A practical reference for engineers working with Microsoft Fabric. Whether you are preparing for a role, onboarding to the platform, or running Fabric in production, these patterns will save you time. 250 scenarios covering the full data engineering stack. Each one explains the concept, the common mistake, and the right approach.
Huemul BigDataGovernance, es una framework que trabaja sobre Spark, Hive y HDFS. Permite la implementación de una estrategia corporativa de dato único, basada en buenas prácticas de Gobierno de Datos. Permite implementar tablas con control de Primary Key y Foreing Key al insertar y actualizar datos utilizando la librería, Validación de nulos, largos de textos, máximos/mínimos de números y fechas, valores únicos y valores por default. También permite clasificar los campos en aplicabilidad de derechos ARCO para facilitar la implementación de leyes de protección de datos tipo GDPR, identificar los niveles de seguridad y si se está aplicando algún tipo de encriptación. Adicionalmente permite agregar reglas de validación más complejas sobre la misma tabla.