About this project

# The Data Engineering Handbook This repository serves as a comprehensive, curated resource hub for anyone looking to become a data engineer. It aggregates a wide range of learning materials and professional resources, making it a valuable starting point for both beginners and experienced practitioners. ## Key Features - **Learning Roadmaps**: Provides a clear 2024 roadmap for breaking into data engineering, along with structured boot camps for absolute beginners and intermediate learners. - **Curated Book List**: Features over 25 recommended books, highlighting top picks like "Fundamentals of Data Engineering," "Designing Data-Intensive Applications," and "Designing Machine Learning Systems." - **Community Directory**: Lists over 10 active communities, including DataExpert.io Discord, Data Talks Club Slack, and Data Engineer Things, offering networking and support opportunities. - **Tool & Company Index**: Organizes a vast array of companies and tools by category, such as Orchestration (Airflow, Dagster, Prefect), Data Lake/Cloud (Databricks, Snowflake, Apache Iceberg), Data Quality (dbt, Great Expectations), and Data Integration (Airbyte, Fivetran). - **Educational Content**: Includes links to blogs from major tech companies (Netflix, Uber, Databricks), important whitepapers, and a list of podcasts. - **Creator Directory**: A comprehensive list of data engineering influencers and educators across YouTube, LinkedIn, X/Twitter, Instagram, and TikTok, with follower counts. - **Practical Resources**: Offers sections for hands-on projects, interview preparation advice, and newsletters for continuous learning. ## How to Use 1. **Start Here**: If new to the field, follow the provided 2024 roadmap. 2. **Explore Sections**: Navigate the repository's markdown files (e.g., `books.md`, `communities.md`, `projects.md`) for detailed lists. 3. **Join Communities**: Connect with peers in the recommended Discord and Slack communities. 4. **Dive Deeper**: Use the categorized company and tool lists to research specific technologies. This handbook is an excellent, continuously updated reference for anyone serious about a career in data engineering.