As a Data Engineer in Germany 🇩🇪 one thing I learned: companies care more about what you can BUILD than what you can list on a CV.
If you’re serious about Data Engineering, build these 5 projects:
Batch ETL Pipeline
Real-time Kafka Pipeline
Spark Data Processing Project
Cloud Data Warehouse
End-to-end Analytics Pipeline
5 strong projects > 50 certificates.
Before your behavioral interview, prepare 5 stories:
→ Biggest success
→ Biggest failure
→ Conflict
→ Leadership
→ Difficult deadline
Use:
Situation → Task → Action → Result
One good story can answer multiple questions.
Before your interview, research:
→ What the company builds
→ Main products
→ Customers
→ Competitors
→ Recent news
→ Company culture
→ Team/department
→ Interviewer’s background
Never enter an interview knowing only the company name.
Before your interview, open the JD again.
Mark every requirement:
→ 🟢 I know it well
→ 🟡 I know the basics
→ 🔴 I don’t know it
Revise RED first.
The job description is basically your interview cheat sheet.
Before your interview, prepare for:
“What are your salary expectations?”
Don’t answer randomly.
→ Research the market range
→ Know your target salary
→ Know your minimum privately
→ Consider the full package
→ Give a reasonable range
→ Stay open to negotiation
Example:
“I’m targeting €70K–€80K, depending on the overall package.”
Know your worth before they ask.
Before your interview, choose ONE project and know:
→ Problem
→ Architecture
→ Tech stack
→ Your contribution
→ Biggest challenge
→ Failure you faced
→ Trade-offs you made
→ Final impact
One project explained deeply > five projects explained vaguely.
@mikeydsoftware The skill is shifting from writing every line to understanding systems and solving the right problems.
AI can code, but developers still need to know what to build and why.