The process was structured and professional.

It started with a recruiter screening where we discussed my experience, especially around data engineering tools like AWS, Python, and Spark.

After that, I had a technical phone interview with real-world coding and SQL problems. They focused a lot on data pipeline design, performance tuning, and system design.

Next was the onsite (or virtual onsite) round, which included 4-5 interviews.

Each one tested different areas:

• Cloud data architecture
• ETL optimization
• Behavioral questions on team leadership and problem-solving

One round was specifically about coding in Python and another was focused on SQL queries and data modeling.

They asked me to design a real-time data pipeline that ingests streaming data, processes it, and makes it available for analytics. This was basically testing my hands-on knowledge with tools like Kafka, Spark Streaming, and AWS services such as Kinesis, Glue, and Redshift.