The only good thing is that the stocks you get will be good.
No new technology in the data engineering field. It's all about their own tools, which are of no use outside the company. There's very little design work, just modifying existing SQL or writing new SQL queries. There's no ETL, nor any good Hadoop-related tools the company has. Everything will be taken care of by SDEs, so there's no scope for DEs to learn. There's a lot of operations work.
The interview process begins with resume screening for the first round. Shortlisted candidates receive a test link with 12 sections covering Python, Linux, SQLite, SQL, and other topics, plus one DSA question. Those who clear this round are schedul
First, a written test with aptitude and a coding round. Then, two rounds of technical interviews. After clearing the first round, you will get a call for the second round. It was an on-campus placement.
I have one technical round, followed by a one-hour round. They were satisfied with my performance. They asked questions similar to inverting a binary tree and buying/selling stocks, which I answered. However, one question I was not able to do.
The interview process begins with resume screening for the first round. Shortlisted candidates receive a test link with 12 sections covering Python, Linux, SQLite, SQL, and other topics, plus one DSA question. Those who clear this round are schedul
First, a written test with aptitude and a coding round. Then, two rounds of technical interviews. After clearing the first round, you will get a call for the second round. It was an on-campus placement.
I have one technical round, followed by a one-hour round. They were satisfied with my performance. They asked questions similar to inverting a binary tree and buying/selling stocks, which I answered. However, one question I was not able to do.