J'ai postulé en ligne. J'ai passé un entretien chez Apollo.io
Entretien difficile
Candidature
J'ai postulé via la recommandation d'un employé. Le processus a pris 4 semaines. J'ai passé un entretien chez Apollo.io en juin 2020
Entretien
got to meet the executive and leadership team. very open ended interview which assess raw skills rather than specific knowledge. the team is very passionate and i feel that the company is moving towards a great direction.
There were total of four rounds
- first round consist of easy to medium leetcode question
- second round consist of React machine coding round
- third round consist of debugging round with react and redux
- fourth round consist of behaviour round
J'ai passé un entretien chez Apollo.io (Bengaluru)
Entretien
Initial screening through coderbyte. there were 3 question. two of them were problem solving & one from react. need to solve with in 50 min. all 3 questions. In order to move
to next round
Questions d'entretien [1]
Question 1
Screening through coderbyte. there were 3 questions
J'ai postulé en ligne. J'ai passé un entretien chez Apollo.io (San Francisco, CA)
Entretien
The interview process was quite convoluted. It involved multiple rounds that seemed disorganized and redundant. First, I had a screening call with HR, which was followed by a technical assessment. The technical questions focused on coding challenges and system design, but after completing that round, I was unexpectedly asked to repeat some similar tasks in the second technical round. Moreover, I was introduced to an entirely different interviewer who seemed unaware of my previous discussions. There was also a lengthy discussion on data crawling methods, especially LinkedIn crawling, which felt out of scope for the role I applied for, and raised some legal and ethical questions. The entire process took several weeks with long gaps between communications, which made it hard to follow and frustrating.
Questions d'entretien [1]
Question 1
Can you explain how you would set up a LinkedIn crawling system to collect large amounts of user data efficiently?