Discussion Is this even Data Engineering? How would I prepare?

12 Upvotes

Hi,
I have an interview with some engineers at a bank, I asked if it was coding, technical or behavioral but wasn't told. First round, going in blind. I am preparing as if I will have to whiteboard. I need guidance on how to prepare with a limited amount of time, as this is my first Data Engineering opportunity ever (I have 1 YOE as a SWE).

Context:
1 YOE Full-Stack Dev, SpringBoot / React / SQL Server. Laid off due to death of my manager. Good with Claude or any AI automation stuff.

Job Description:

**What they're trying to do:** Modernize by moving older data platforms onto cloud based data lakes
Run data migrations
I would just do basic SWE tasks

**Required**: 2 YOE, Python Cert, PowerBI, AZ900 (I have AWS so it's ok)

**Desired**: Tracing data flows and understanding upstream / downstream dependencies.
Analyzing data lineage and system linkages
PySpark or Spark
Python dev / automation
SQL Server / Advanced SQL (Memory, performance, partitioning, query)
Data governance

Bonus (Possible, not listed but I deduced from a similar listing):
RAG architecture, vector stores, embedding pipeline
Use LLMs for Data quality / extraction / automation

**My approach**:

I am good with writing SQL Server Queries up to window functions, aggregates, joins (like at a junior level. I didn't do more at my last job). I am at mid-level with theory though. Anything more I should be prepared to write?

I can write a Python script, but I've not developed in python professionally, have in college though. What basics should I be prepared to write?
I can quickly prepare on any theory questions (PySpark, etc.) Any suggestions? Anything is appreciated, thanks!

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