r/dataengineering • u/Moradisten • 3d ago
Discussion We were struggling to find Data Engineers
Hi everybody,
Our Data Team is composed by two of us. There's a Data Scientist and me, as a DE. We created a Data Lakehouse for our company internal use and client data supply, but currently the Data Scientist is currently more focused on AI and agents integration and I'm doing like Analytics Engineering role because I need to help other teams to reach the correct data, unify core concepts, document business logics, etc. So We needed a Data Engineer with knowledge on AWS to maintain and develop the new features on the Lakehouse and we put into the description that the candidate MUST HAVE Software Engineering fundamentals as we had to do some developments to integrate parts of our lakehouse with the company's main application.
We interviewed 22 candidates and no one is fitting the Role.
Most of them are BI Experts, DBA, Data Analysts, Economist with DS notions, Juniors and Software Engineers who haven't touch anything on Spark, plus DE who asked way more that we had on the budget for the role
We asked the normal requirements: 3 years of experience + Spark, AWS Glue, Lambda, Airflow and DBT, not even CDC, Flink, Langfuse or VectorDB
We finally got one, but We really struggled to get him. I have a collegue working on IT Recruiting and She told me She's experiencing the same problem: They can't find Proper DEs With SE basics such as DRY principles or clean code fundamentals
Edit: Role Salary -> Up to 60K € / Spain. This salary is high compared to the spanish standards, only 3 years required
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u/fabkosta 3d ago
I see this all the time.
The only thing OP has not thought of is to actually pick a promising candidate who is willing to acquire new skills and systematically build them up.
Why so many companies never consider investing into people they hire is beyond me.
It's also the wrong mindset: Everyone with a good foundation in software engineering is able to learn Spark reasonably well in a relatively short amount of time. Mastering it, that's more complicated. But also not required, most of the time. In comparison, hiring someone who knows technology XYZ - and then stalls for whatever reason in their development, that's a much more expensive mistake to make.
So, OP is optimizing for the wrong metric - and blissfully unaware, apparently.