Envié una solicitud electrónica. El proceso duró 4 semanas. Acudí a una entrevista en Cloudera
Entrevista
Friendly, relaxed verbal contact with internal recruiters during HR screen. They made constructive suggestions about resume tuning before forwarding for technical screening. HR emphasized likely topic areas for the technical screen, and offered postponement of the technical interview to allow for more study time. Technical screener was equally personable and friendly, but clearly held high expectations for accurate & immediate responses to their technical challenge questions; actual technical emphasis areas differed somewhat from HR's predictions. Came out with a positive impression of the organization and people, based on this experience.
Preguntas de entrevista [1]
Pregunta 1
Diagnostic questions about system errors encountered in the field related to Linux system administration and Java run time. Advanced how-to questions on Java, scripting, databases, tying into system performance.
First step is Initial Screen interview, The Second interview by Hiring Manager, The Third interview by solution architect(its mainly deep dive technical conversation) , Fourth and final hands on exercise followed by final presentation
Preguntas de entrevista [1]
Pregunta 1
They normally asked about the relevant big data experience. As I come from Spark experience discussed spark tuning.
Fairly straightforward, phone screen, into 1-2 rounds of peer/manager screening, panel at the end. May or may not include a technical exercise - in recent times this seems to have been abandoned as a practice
Preguntas de entrevista [1]
Pregunta 1
Positioning of a product based on a customer scenario
Solicité el puesto a través de un captador. El proceso duró 4 meses. Acudí a una entrevista en Cloudera (Ámsterdam) en ene 2022
Entrevista
The procedure was fun and caring for people! there is a lot of freedom to talk about and the questions are very technical. Very nice and there are specialist people who they allow you to talk with any time.
Preguntas de entrevista [1]
Pregunta 1
- if you would have a model deployed in production using machine learning - how would the company use it to add value to its customers without touching the model?
