I worked as a financial analyst for 5 years, spending most of my time in Excel. When I discovered Python could automate my reporting tasks, I was hooked.

Started with Python for data analysis, then learned SQL, pandas, and eventually moved into big data technologies like Spark. My finance background made the transition to data engineering natural.

The interview process was tough - lots of technical questions about distributed systems and data pipelines. I studied system design religiously and practiced coding problems daily.

What set me apart was my ability to understand business requirements and translate them into technical solutions. Many engineers can code, but fewer can bridge the gap between business and technology.

On the interview

Heavy focus on SQL and data pipeline questions. Interviews included: technical SQL challenges, system design for data workflows, and case studies using real business data.