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A curated handbook of links and resources for learning data engineering: roadmaps, bootcamp materials, books, communities, company tooling lists, blogs, whitepapers, and a directory of data engineering content creators.
A curated handbook of links and resources for learning data engineering: roadmaps, bootcamp materials, books, communities, company tooling lists, blogs, whitepapers, and a directory of data engineering content creators.Is this a course, a reading list, or something else?It's mainly a curated reading list and index of other resources (bootcamps, books, blogs, whitepapers, tools), not a self-contained course with its own lessons.
It's mainly a curated reading list and index of other resources (bootcamps, books, blogs, whitepapers, tools), not a self-contained course with its own lessons.Where should a beginner start?Start with the 2024 'breaking into data engineering' roadmap, or jump into the 4-week free beginner bootcamp or 6-week intermediate bootcamp introductions and software-needed guides.
Start with the 2024 'breaking into data engineering' roadmap, or jump into the 4-week free beginner bootcamp or 6-week intermediate bootcamp introductions and software-needed guides.Do I need any paid tools or accounts to follow this?No paid tools are required; it links to free bootcamps (including a free Databricks AI boot camp) and free community Slack/Discord servers.
No paid tools are required; it links to free bootcamps (including a free Databricks AI boot camp) and free community Slack/Discord servers.Is this list curated or does anything get added?It has some quality bar for the social media section — creators need at least 5,000 followers somewhere to be listed — but otherwise it's a broad aggregation of many tools and companies without strict vetting criteria described.
It has some quality bar for the social media section — creators need at least 5,000 followers somewhere to be listed — but otherwise it's a broad aggregation of many tools and companies without strict vetting criteria described.Who is this handbook aimed at?Aspiring and practicing data engineers, from beginners following the roadmap/bootcamps to those preparing for interviews or wanting to learn via books, newsletters, and communities.
Aspiring and practicing data engineers, from beginners following the roadmap/bootcamps to those preparing for interviews or wanting to learn via books, newsletters, and communities.What kind of hands-on practice is included?The repo points to a separate projects section for hands-on examples, in addition to the theory-heavy books, whitepapers, and blog links.
The repo points to a separate projects section for hands-on examples, in addition to the theory-heavy books, whitepapers, and blog links.What topics do the recommended books cover?The top picks include 'Fundamentals of Data Engineering', 'Designing Data-Intensive Applications', and 'Designing Machine Learning Systems', covering both core data engineering and ML systems design.
The top picks include 'Fundamentals of Data Engineering', 'Designing Data-Intensive Applications', and 'Designing Machine Learning Systems', covering both core data engineering and ML systems design.What kind of tools does the handbook catalog?It lists companies and tools across orchestration (Airflow, Dagster, Mage), data lakes/warehouses (Snowflake, Databricks, Iceberg), data quality (dbt, Great Expectations), data integration (Fivetran, Airbyte), and modern OLAP engines (ClickHouse, DuckDB, StarRocks).
It lists companies and tools across orchestration (Airflow, Dagster, Mage), data lakes/warehouses (Snowflake, Databricks, Iceberg), data quality (dbt, Great Expectations), data integration (Fivetran, Airbyte), and modern OLAP engines (ClickHouse, DuckDB, StarRocks).What are similar projects?awesome-bigdata, data-engineer-roadmap, SDE-Interview-and-Prep-Roadmap, Best-websites-a-programmer-should-visit, Awsome-Front-End-learning-resource, awesome-design-patterns, full-stack-data-engineering, awesome-system-design-resources
awesome-bigdata, data-engineer-roadmap, SDE-Interview-and-Prep-Roadmap, Best-websites-a-programmer-should-visit, Awsome-Front-End-learning-resource, awesome-design-patterns, full-stack-data-engineering, awesome-system-design-resourcesWhich topics is it in?bigdata, data-warehouse, data-quality, databases, roadmap, data, data-engineering, big-data, interview-questions, interview, career, jupyter notebook
bigdata, data-warehouse, data-quality, databases, roadmap, data, data-engineering, big-data, interview-questions, interview, career, jupyter notebook