Synthesized from 19 candidate submissions for ALL.
Jupiter Money maintains a consistent interview process generally perceived as average in difficulty, heavily prioritizing deep domain expertise in SQL for data-oriented roles and practical project experience for engineering roles. Candidates should expect a mix of technical deep-dives into their past work, core computer science fundamentals, and rigorous database query assessments.
The candidate, with 3 years of experience and currently working as a Backend SWE2 at a fintech company, went through four rounds: DSA, LLD, HLD, and HM. The process included designing systems like a chess game, typeahead search, and Instagram newsfeed. No feedback was received, and the candidate assumed rejection.
An online assessment round conducted by a third-party site with two questions: finding the number of islands in a matrix and finding the first missing positive element in an array.
Find the number of islands in a matrix where 1 represents an island and 0 represents water.
Find the first missing positive element from an array.
The candidate was asked to design the Low-Level Design (LLD) of a chess game.
Design the Low-Level Design of a chess game.
The candidate was asked to design a typeahead search system similar to Google's search.
Design a typeahead search system similar to Google search.
The round included behavioral questions followed by a task to design the High-Level Design (HLD) of an Instagram newsfeed.
Design the High-Level Design of an Instagram newsfeed.
The interview process for the Decision Scientist Intern role was of average difficulty and focused on basic SQL concepts.
The interview focused on SQL fundamentals.
Difference between having and where
Interview Digest