Data Engineering

Recent Data Engineering articles

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9 articles

Discover our latest articles and guides on Data Engineering

Delta Lake vs Apache Iceberg data lakehouse comparison
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Delta Lake vs Apache Iceberg in 2026: Lakehouse Architecture and Interview Questions

Compare Delta Lake and Apache Iceberg table formats for data lakehouse architecture. Covers ACID transactions, partition evolution, time travel, and common interview questions.

Snowflake architecture diagram showing storage, virtual warehouse compute, and cloud services layers
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Snowflake in 2026: Architecture, SQL and Data Engineer Interview Questions

A 2026 guide to Snowflake architecture for data engineers: how storage and compute separate, how virtual warehouses and micro-partitions work, and the interview questions that test production experience.

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.