HashedIn by Deloitte Interview Experience
Summary
I recently completed a comprehensive interview process for a Python/Backend + GenAI role at HashedIn by Deloitte, spanning DSA, SQL, System Design, and Managerial discussions, which culminated in an offer discussion.
Full Experience
I connected with the recruiter directly through LinkedIn, which initiated my interview process for the Python/Backend + GenAI role at HashedIn by Deloitte. The journey was structured into three distinct rounds.
Round 1: DSA + SQL (Online Coding + Technical Q&A)
This initial round evaluated my problem-solving skills with two DSA coding challenges and two SQL questions. The coding problems included the classic Best Time to Buy and Sell Stock, where I needed to find the maximum profit from a single transaction, and Search in a 2D Matrix, for which I applied an efficient binary search strategy across sorted rows and columns. For SQL, I was tasked with a problem requiring me to Swap Sex of Employees within a table. This round primarily focused on my familiarity and consistency with common interview patterns.
Round 2: LLD + HLD Discussion (System Design)
This round proved to be the most engaging and challenging. My task was to design a multi-tenant e-commerce platform, conceptually similar to Amazon. The design needed to address several critical aspects: supporting multiple vendors with separate product catalogs, maintaining shared infrastructure with proper isolation, and ensuring scalability, caching, availability, and partitioning. We delved deep into API design, database schema choices, and the trade-offs between monolith versus microservices architectures. I also had to demonstrate how to handle high read/write traffic. Key discussion points included tenant isolation strategies, selecting between SQL and NoSQL databases, designing core components like cart, order, and product catalog systems, incorporating cache layers using Redis, implementing event-driven flows with Kafka, and considering rate limiting, throttling, API Gateway, and various deployment & scaling assumptions. This round was a thorough test of my architectural thinking, clarity in communication, and ability to weigh design trade-offs.
Round 3: Managerial + Behavioral Round
The final round was conducted by a manager and focused less on pure technical skills and more on my fitment within HashedIn’s engineering environment. The discussions revolved around my previous project experience, my sense of ownership, and my approach to problem-solving. I shared instances of how I handled production issues, times I worked effectively under pressure, and my strategies for conflict resolution within a team. My motivation for switching roles was also explored. Overall, this round aimed to assess my cultural alignment, communication skills, and mindset.
After successfully navigating all rounds, I proceeded to the salary discussion phase.
Interview Questions (9)
Given an array prices where prices[i] is the price of a given stock on the i-th day, find the maximum profit you can achieve. You may complete at most one transaction (i.e., buy one and sell one share of the stock).
Write an efficient algorithm that searches for a target value in an m x n integer matrix. This matrix has the following properties: Each row is sorted in non-decreasing order. The first integer of each row is greater than the last integer of the previous row. My approach involved an efficient binary search over sorted rows/columns.
I was given a database table containing employee information and asked to write an SQL query to swap the 'sex' column values (e.g., 'm' to 'f' and 'f' to 'm').
I was asked to design a multi-tenant e-commerce platform similar to Amazon. The design needed to support multiple vendors (tenants), each having separate product catalogs, shared infrastructure with isolation, scalability, caching, availability, and partitioning. Key aspects discussed included API design, database schema, trade-offs between monolith vs microservices, and handling high read/write traffic. We went deep into tenant isolation strategies, choice of database (SQL vs NoSQL), designing cart, order, and product catalog, cache layers (Redis), event-driven flow using Kafka, rate limiting, throttling, API Gateway, and deployment & scaling assumptions.
I was asked to walk through one of my recent projects, detailing its purpose, my contributions, challenges faced, and outcomes.
A question on my approach and methodology for debugging production issues and ensuring quick resolution.
I was asked to describe situations where I had to work under pressure and how I managed them.
A question about how I handle and resolve conflicts within a team environment.
I was asked about my motivations for seeking a new role and why I was interested in HashedIn by Deloitte.