Blog
Data Engineering Portfolio: 5 Projects That Get Hired
Five end-to-end data engineering projects—streaming, ETL, warehouse, lakehouse, and observability—to showcase production-ready skills.
How to Learn SQL for Data Engineering: A Roadmap
Three-phase SQL roadmap for data engineers: master querying and DDL/DML, data warehousing and modeling, then optimization, testing, security and hands-on projects.
How to Build End-to-End Databricks Declarative Pipelines
Learn how to build end-to-end Databricks declarative pipelines using LakeFlow Spark for efficient data engineering and incremental processing.
Complete Guide: Notebook-to-Pipeline Data Engineering
Learn how to build efficient data pipelines with Python using notebooks. A complete guide to modern data engineering with Snowflake.
How AI Engineers Can Build Faster and Advance Careers
Discover how AI engineers can build faster, leverage cutting-edge tools, and advance their careers with expert insights and strategies.
Build an End-to-End DBT + Snowflake Pipeline
Learn how to create a complete DBT + Snowflake pipeline from scratch, including incremental loads, metadata-driven pipelines, and star schemas.
Databricks vs Snowflake: Which Platform to Learn First
Compare Databricks and Snowflake to choose which to learn first—Databricks for ML and engineering; Snowflake for SQL analytics and BI.
Databricks vs Snowflake: Cost Efficiency in Embedded Analytics
Compare pricing and scaling for Databricks and Snowflake in embedded analytics—compute, storage, and which workloads they suit best.
7 Essential Skills Every Data Engineer Needs
A concise guide to seven core data engineering skills: SQL, Python, data modeling, ETL/ELT, cloud platforms, governance, observability, and communication.
Data Lake Modeling: Compressing 100 TBs to 5 TBs with Parquet
Discover how Airbnb optimized data lake modeling to compress 100 TBs into 5 TBs using Parquet and run-length encoding techniques.
Tech Career Path Selector
Not sure which tech career fits you? Take our free Career Path Decision Tool to discover your best role in Data Engineering, AI, and more!
How to Transition into Data Engineering in 2026
A pragmatic roadmap to transition into data engineering: key skills, tools, cloud stack, and a 6–12 month plan to build production-ready pipelines.