---
title: Delta Lake and Spark Lakehouse Webinar
canonical: "https://data-driven.com/blog/deep-dive-into-building-a-data-lakehouse-with-delta-lake-and-spark/"
pubDate: "2021-10-15T00:00:00.000Z"
updatedDate: "2026-08-25T00:00:00.000Z"
description: "An archived Sydney Databricks Meetup session on building an ingestion pipeline with Delta Lake and Spark, with source details retained."
tags: [databricks-meetup, advanced, databricks, delta-lake, spark]
categories: [databricks]
---

Jonathan Neo presented this lakehouse session to the Sydney Databricks Meetup in October 2021. The talk connected Delta Lake and Spark to an end-to-end ingestion workflow.

This page is a session record. The old download form did not contain a recoverable slide or recording link, so it has been removed rather than left as a working promise.

## Published session outline

- The components of a lakehouse architecture.
- How Delta Lake and Spark supported the architecture shown in the talk.
- An end-to-end data-ingestion pipeline.

Current Databricks runtimes, table-management features, and architecture guidance have changed since the event. Use the session as historical context, then check current product documentation before implementing the pattern.

## Presenter record

The event listed <a href="https://www.linkedin.com/in/jonneo/" target="_blank" rel="noopener noreferrer">Jonathan Neo</a> as the presenter. His biography and job title on the original page belong to 2021 and are not repeated as current facts.

The session was hosted through the <a href="https://www.meetup.com/Sydney-Databricks-User-Group" target="_blank" rel="noopener noreferrer">Sydney Databricks Meetup</a>.
