Interview summary of last 6 months (Microsoft + Salesforce + Oracle + Flipkart + Walmart + Tekion)

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interview experience
· Senior Software Engineer· 7y exp
August 23, 2026 · 0 reads

Summary

I attended multiple interview rounds across several companies over the past six months, covering OA, DSA, LLD, HLD, and behavioral questions. I received mixed outcomes, with some offers and several rejections.

Full Experience

YOE : 7 years Role : Senior Software Engineer

Salesforce

  • OA - 1 medium + 1 Hard bitmasking question
  • Screening (1.5 hrs) - 2 medium DSA questions (30 mins) + 1 LLD question (1 hr)
  • R1 onsite (1.5 hrs) - 1 DSA question + LLD (Connect 4 problem). Shortest path from node n to all nodes will be marked as x (blue color). Return all possible paths from 1 to n such that x for that node is less than previous node. (2 times Dijkstra in 1 problem).
  • R2 onsite (1.5 hrs) - Design HLD of notification service (NotificationPriority-High/low, Template, UserPreferences, User-DND). Scalability, Resilience, Availability. Discussed Kafka in depth.
  • R3 HM (1.25 hr) - Behavioral questions and system design of messaging/temporal.

Salesforce (second round)

  • R1 (1 hr) - 2 DSA problems - medium level LeetCode
  • R2 (1 hr) - LLD of JobScheduler. Use delay instead of polling. (Rejected)

Oracle Cloud

  • DSA - question on next greater element.
  • HLD - MessageScheduler (similar to JobScheduler). At scheduled time, message can be delivered to 1‑10k users. Delivery should be within 1 sec of scheduled time.
  • Bar raiser - Project discussion + standard behavioral questions.
  • HM round - Project + networking questions (ping, TCP vs UDP, Linux networking).

Oracle Health (SSE + AI role)

  • Screening - 2 medium DSA questions.
  • HLD - Rate Limiter (no follow‑up asked).
  • DSA - Place k buildings on n × m matrix. Distance from every empty location to the closest building is x. Buildings should be placed so that the maximum of all x is minimized. (Expected brute‑force, n,m ≤ 8).
  • Bar raiser - Project + standard behavioral questions.
  • HM round - Project discussion (rejected).

Walmart

  • HLD (asked in 2 different roles over 1 year) – Google Docs, Malicious content checking on blob storage (AWS S3, Azure), Rate Limiter for Big Billion Sale.
  • LLD + Java - Naukri Portal (30 mins). Focus on Person, Job @ManyToMany relationship. Various questions on Java, K8s, Docker, SpringBoot.
  • DSA - basic medium level (top 75 questions).
  • Overall advice: know Java + SpringBoot thoroughly, DSA medium is enough, LLD + HLD (top 10) is sufficient.

Microsoft Azure

  • 2 OA questions.
  • R1 - DSA (30 mins – Rotten orange) + OS concepts + project questions.
  • R2 - DSA (40 mins – basic tree question + long read) + OS concepts (paging, virtual memory).
  • R3 - HLD (1.5 hrs) – OTP service (multi‑tenant) + Notification service.
  • AA (1.5 hrs) – 3 questions on physical & virtual addressing on different devices (RAM, SSD, Hard disk).
  • AA (2nd team – 30 mins) – Web crawler (System Design) + inverted indexing + 2 behavioral questions.

Flipkart

  • Machine coding (90 mins) – Food delivery service. Implement all functionalities (place/cancel/pickup order, etc.) with OOP concepts, extensibility, proper format.
  • 2 medium DSA – topological sorting + one more.
  • HLD – Rate Limiter (deep discussion).
  • Expectation: know Rate Limiter components deeply, basic DSA, top 10 LLD + HLD.

Tekion

  • DSA – medium level questions.
  • LLD – Workflow orchestrator.

Interview Questions (3)

1.

Connect 4 Shortest Path Problem

Data Structures & Algorithms

Given a graph representation of a Connect 4 board, each node n has a value x (colored blue). Find all possible paths from node 1 to node n such that the x value of each successive node is less than that of the previous node. The solution requires running Dijkstra's algorithm twice within a single problem.

2.

Next Greater Element

Data Structures & Algorithms

For each element in an array, find the next element to its right that is greater than it. If no such element exists, return -1 for that position.

3.

Place k Buildings to Minimize Maximum Distance

Data Structures & Algorithms

Given an n × m matrix where some cells are empty, place k buildings on the grid (n,m ≤ 8). For each empty cell, compute the distance to its nearest building (distance = x). Choose building positions so that the maximum of all x values across the grid is minimized. Expected solution is brute‑force due to small constraints.

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