SDE 2 @ Capillary Technologies

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capillary technologies
· SDE 2· 4y exp
July 23, 2026 · 0 reads

Summary

I interviewed for an SDE 2 position at Capillary Technologies, completed three rounds in a single day, and received an offer which I ultimately declined due to compensation.

Full Experience

This is the interview experience for SDE 2 at capillary, all 3 interviews were on same day it was a virtual drive on weekend. Process for interviews was smooth.

Round 1: DSA (with SDE 2)

  • Basic Theory
  • Delete without head pointer (GFG Medium)
  • Top View of Binary Tree (GFG Medium)

Round 2: Design (with SDE 3)

  • Design a System that handles the processing of billions loyalty data and helps generate the meaningful insight on that data.

Round 3: Past Experience and Project Deep Dive (with ATL/TL)

  • Major project in your past exp.
  • Your contribution and challenges and conflict resolution.

Verdict: I joined but you shouldn't, they offer very less(compensation) and demand a lot(work/time).

Comp: 25 Base + 1 Bonus YOE: 4 Interview Day: June 2025

Interview Questions (3)

1.

Delete node without head pointer

Data Structures & Algorithms·Medium

Given a reference to a node in a singly linked list (the node to be deleted) and no access to the head of the list, delete that node from the list. You must achieve this in O(1) time and O(1) extra space. The typical solution copies the data from the next node into the current node and bypasses the next node.

2.

Top View of Binary Tree

Data Structures & Algorithms·Medium

Given a binary tree, return the list of node values visible when the tree is viewed from the top. For each horizontal distance from the root, only the first node encountered during a level order traversal is part of the top view.

3.

Design a System for Processing Billions of Loyalty Data

System Design

Design a scalable system that can ingest, store, and process billions of loyalty‑program data records and generate meaningful insights (e.g., customer segmentation, reward calculations, real‑time recommendations). Consider data ingestion pipelines, storage solutions, processing frameworks, APIs for querying insights, and handling high throughput and low latency requirements.

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