Questions & Answers

Why Google Cloud Platform instead of AWS/Azure?

Key reasons:

  1. $300 free credits for new accounts vs. AWS’s limited free tier
  2. Better tool access. No service limitations during the free trial
  3. Historical compatibility. dbt worked better with BigQuery when the course launched

For the project, you can use any cloud provider.

Can I get a DE job without a degree?

Short answer: YES.

Multiple success stories include:

  • Students who landed jobs through the course network
  • Bruno (no formal degree, now Senior DE at US companies)
  • Career switchers from analytics

The key is:

  • Strong portfolio of projects
  • Networking (learning in public helps)
  • Consistency and going beyond basics

Is 31 “too old” to start?

Absolutely not. You’re still early in your career. In Germany, many start at 30+ after extended education. The industry cares about skills, not age.

Tip: Don’t put age on your CV to avoid unconscious bias.

How much time does the course take?

  • 7 weeks for modules
  • 2-3 weeks for project
  • Plan for 10-15 hours per week for optimal results

What’s NOT covered (the other 80%)?

Bruno highlighted areas the course doesn’t cover but working DEs encounter:

  • Polars: Modern pandas alternative for data manipulation
  • Delta Lake / Apache Iceberg: Advanced table formats for data lakes
  • Snowflake / Redshift / ClickHouse: Other data warehouses
  • dbt incremental models: Optimizing dbt for large datasets
  • Apache Flink: Real-time streaming (but Zak covers this in Module 6)
  • Data governance & catalogs: DataHub, Unity Catalog

The course covers the essential 20% that will handle 80% of real-world work. The rest comes with experience.

Final Thoughts

Data engineering is a field that’s “5 feet deep and 50 miles wide.”

Remember:

  • Ask questions (after checking the Q&A)
  • Learn in public
  • Help your peers in Slack
  • Don’t get discouraged. It gets challenging.
  • You got this.