Lauri Koobas, ex-Microsoft and currently Head of Data Platform at Bondora, shed insights on data engineering - from early startup to scaling.

We mostly focused on analytics and building data warehouse - real-world challenges from both data engineering and software engineering sides. We also discussed GDPR and PII challenges when dealing with data.

You can find video version on MapForEngineers YouTube channel: https://www.youtube.com/@mapforengineers

Annotated chapters in timeline:

00:00:00 Sneak peek of episode

00:01:21 Episode overview

00:02:44 Introduction, Lauri's background

00:20:48 Starship robots: huge amount of data there

00:23:37 Data lake, data warehouse, data lakehouse

00:26:44 Devil is in the details: timestamps, texts, character sets...

00:49:44 Moving data from prod to data warehouse

00:53:09 Analytics tools: PostHog, Amplitude, Redash, Databricks

01:00:15 Analytics tools vs real-time monitoring like Prometheus/Grafana

01:04:15 Usability matters: each tool for its job

01:06:38 Startup grows: needs in data analytics

01:11:09 Multiple data sources: when data warehouse really begins

01:19:55 Data and (de-)coupling: software engineers should not be blocked by analytics

01:22:51 Data ETL

01:24:59 Changes in data model: multi-phase migrations

01:29:38 Change data capture, incremental imports

01:34:21 Should analytics have new data in real time? Maybe not?

01:39:02 Importing data into DWH through business events

01:43:37 When DWH subscribes to business events, data model can evolve freely

01:47:16 Quick recap what we discussed so far

01:52:25 GDPR and Data Compliance: start early

01:56:05 PII data: know exactly where you store it, control it well

02:03:37 Lauri's books recommendations on data engineering - Kimball

02:07:18 Lauri's podcast on data engineering, in Estonian

02:08:28 Wrap up

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