# Databricks is abstracting away physical data engineering controls

DevFeed: [Databricks is abstracting away physical data engineering controls](<https://devfeed.tech/articles/databricks-is-no-longer-about-tuning-knobs-27242.md>)

Original publisher: [Read original article](<https://blog.dataexpert.io/p/databricks-is-for-data-analysts-not>)

Author: Zach Wilson

Published: 2026-02-24T01:03:11Z

Content type: opinion

Language: en

Sources: [DataExpert.io Newsletter](<https://devfeed.tech/sources/dataexpert-io-newsletter.md>)

Topics: [databricks](<https://devfeed.tech/topics/databricks.md>), [data-engineering](<https://devfeed.tech/topics/data-engineering.md>), [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>)

Tags: [architecture](<https://devfeed.tech/tags/architecture.md>), [data-engineering](<https://devfeed.tech/tags/data-engineering.md>), [databricks](<https://devfeed.tech/tags/databricks.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [partition](<https://devfeed.tech/tags/partition.md>), [partitioning](<https://devfeed.tech/tags/partitioning.md>), [sorting](<https://devfeed.tech/tags/sorting.md>), [spark](<https://devfeed.tech/tags/spark.md>)

## AI overview

This opinion article argues that Databricks is shifting away from hands-on data engineering by abstracting physical data modeling through features such as liquid clustering and predictive optimization. It also criticizes Databricks' support for managed Apache Iceberg tables after acquiring Tabular.

## Source excerpt

Databricks abstracts away almost all of the data engineering skills. Liquid clustering is the first place where things will get messy!