---
title: "Lakeflow: A new era of agentic data engineering"
url: https://daily.dev/posts/lakeflow-a-new-era-of-agentic-data-engineering-o3y9hgcdq
source_url: https://www.databricks.com/blog/lakeflow-new-era-agentic-data-engineering
type: article
source: "databricks"
published: 2026-06-16T13:03:27.094Z
updated: 2026-06-16T13:07:08.647Z
tags: ["backend", "data-engineering", "apache-spark", "databricks", "etl"]
reading_time: 8
upvotes: 0
comments: 0
language: en
---

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# Lakeflow: A new era of agentic data engineering

**[databricks](https://daily.dev/sources/databricks)** · 8 min read · 0 upvotes · 0 comments

## Summary

Databricks announced major updates to Lakeflow, its unified data engineering platform, at the Data + AI Summit. Key highlights include: Genie Code AI assistant integrated across ingestion, transformation, and orchestration; Lakeflow Designer (now GA) offering a no-code drag-and-drop pipeline builder; Genie ZeroOps, a new background AI agent for automated pipeline monitoring, root-cause analysis, and fix generation; Lakeflow Connect expanding to 100+ native managed connectors with a free tier (100 DBUs/day); Zerobus Ingest for near real-time high-throughput event ingestion (under 5s latency, up to 100MB/s); Real-Time Mode for Spark Declarative Pipelines now in public preview with end-to-end latencies as low as 5ms; and Lakeflow Jobs adding data-readiness triggers and external orchestration with 40+ operator examples.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.databricks.com/blog/lakeflow-new-era-agentic-data-engineering>

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---

Tags: [#backend](https://daily.dev/tags/backend), [#data-engineering](https://daily.dev/tags/data-engineering), [#apache-spark](https://daily.dev/tags/apache-spark), [#databricks](https://daily.dev/tags/databricks), [#etl](https://daily.dev/tags/etl)

[View this post on daily.dev](https://daily.dev/posts/lakeflow-a-new-era-of-agentic-data-engineering-o3y9hgcdq)