I applied online. I interviewed at BlaBlaCar (Paris)
Interview
Appel avec les RH
Appel avec le directeur
Accueil test technique - modélisation de données et exercice python
Feedback sur le test technique avec 1 AE & 1 DA
Appel avec VP Data
Interview questions [1]
Question 1
Construire un modèle de données pour un cas d'utilisation professionnel
Bonjour !
Nous vous remercions d'avoir pris le temps de nous faire part de vos commentaires et nous sommes heureux d'apprendre que votre expérience a été globalement positive.
Nous apprécions les efforts que vous avez déployés pour postuler au poste d'Analytics Engineer et nous avons apprécié d'apprendre à vous connaître tout au long du processus.
Nous sommes heureux de vous compter parmi les membres de l'équipe et nous espérons que vous apprécierez le voyage !
L'équipe BlaBlaCar.
I received a statistics test that also require reasoning, After i had a HR interview, Then manager interview.
The recrutement process was quick and clear, However, i didn't proceed to the next step
Hello!
Thank you for taking the time to leave such a detailed review.
We appreciate your effort in applying to the Analytics Engineer role and hope you enjoyed the experience.
It was a pleasure to get to know you and we wish you all the best on your journey!
The BlaBlaCar team.
I applied online. The process took 3 weeks. I interviewed at BlaBlaCar in Dec 2023
Interview
• a 45 min video-call with HR
• a 45 min video-call with Data Engineering Manager
• a remote exercise followed by a 90 min video-call with two DE/AEs
• a 30-min with VP data
Interview questions [1]
Question 1
HR interview: motivations, leave & join reasons; collaboration with business people; salary expectation
Manager interview: conflict and disagreement management; project and time management skills (synergy); salary expectation
Technical exercises: Data modelling on Carpool, python coding of an ELT pipeline to load data from API to DB.
Technical interviews: Presentation of your work. your modelling logic, pros and cons of different data modelling methods (Kimball, OBT, data vault, according to your choice); Special focus on analysing leg of journeys and trip stops ; difference of append/truncate data & dbt incremental models, when to use different methods; how to handle slowly changing dimensions; your pipeline alerting methods; Schema changes handling (order of columns; new columns etc.); SQL questions based on your answer (window functions etc.)
VP data interview: your understanding of the position; disagreement and conflict management; your career planning