Data Engineering

Recent Data Engineering articles

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7 articles

Discover our latest articles and guides on Data Engineering

Apache Airflow pipeline orchestration DAGs tutorial 2026
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Apache Airflow in 2026: Pipeline Orchestration, DAGs and Interview Questions

Master Apache Airflow 3.2 with this hands-on tutorial covering DAG authoring with the Task SDK, pipeline orchestration patterns, asset partitions, and real interview questions for data engineering roles in 2026.

dbt data build tool transformations and testing tutorial 2026
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dbt in 2026: Data Transformations, Testing and Interview Questions

Master dbt (data build tool) with this hands-on tutorial covering SQL transformations, layered modeling, testing strategies, and real interview questions for data engineering roles in 2026.

Apache Spark 4 data engineering structured streaming pipeline illustration
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Apache Spark 4 in 2026: New Features, Structured Streaming and Interview Questions

A comprehensive guide to Apache Spark 4.x covering ANSI mode, VARIANT type, Real-Time Mode streaming, Spark Connect, and common data engineering interview questions with code examples.

Apache Kafka streaming architecture with partitions and data flow diagram
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Apache Kafka for Data Engineers: Streaming, Partitions and Interview Questions

Apache Kafka deep dive for data engineers covering streaming architecture, partition strategies, consumer groups, and common interview questions with practical examples using Kafka 4.x and KRaft.

ETL vs ELT data pipeline architecture comparison diagram
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ETL vs ELT in 2026: Data Pipeline Architecture Explained

ETL vs ELT comparison for modern data pipelines. Understand the architectural differences, performance trade-offs, and when to use each approach with Snowflake, BigQuery, and dbt in 2026.

Apache Spark with Python data pipeline tutorial illustration showing data flow and processing stages
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Apache Spark with Python: Building Data Pipelines Step by Step

A hands-on PySpark tutorial covering DataFrame operations, ETL pipeline construction, and Spark 4.0 features. Includes production-ready code examples for data engineers preparing for technical interviews.