How long does the Deepki interview process take?

Most candidates spend between 4 and 8 weeks from recruiter screen to offer. The onsite loop itself runs in a single day or is split across two half-days, with debrief and offer typically within 5 business days after.

How should I prepare specifically for Deepki?

Focus on three things: (1) the company DNA shown above - what they actually grade for, (2) the rounds in your loop, especially the round most candidates underestimate, and (3) drilling on the question types in this guide using a structured framework like CIRCLES or STAR.

Does this apply to engineering or design roles at Deepki?

The DNA stays the same - what changes is the round mix. SWE candidates face coding screens instead of Product Sense; designers face portfolio reviews and design exercises. The "what they value" and behavioral signals carry across all functions.

Other roles at Deepki:Product Manager Software Engineer Sales Supply Chain

Growth · Software Engineer Interview Guide

How to Pass the Deepki Software Engineer Interview in 2026

The Deepki DNA (TL;DR)

The bar-raiser round at Deepki often features a case study on optimizing energy consumption for a commercial building portfolio. This evaluates a candidate's capacity to leverage data from platforms like Deepki Analyze to drive tangible environmental impact, aligning with their core mission.

The Deepki Interview Loop

Your onsite loop will typically consist of 5 rounds.

1
Round 1
Recruiter Screen
Motivation, role fit, logistics.
2
Round 2
Coding Screen
LeetCode-medium algorithmic problems under time pressure.
3
Round 3
System Design
Distributed systems, trade-offs at scale, architecture under constraints.
4
Round 4
Onsite Coding
LeetCode-hard, debugging, code clarity, edge cases.
5
Round 5
Behavioral / Leadership
Past evidence of ownership, influence, resolving conflict.

The Danger Zone: Top Reasons Candidates Fail

Based on our database of Deepki interview outcomes, avoid these common traps:

Focusing on syntax errors instead of logical flaws.
Using a static threshold for deviation without considering external factors.
Inefficiently processing the data stream, e.g., re-scanning the entire history for each new data point.
Underestimating the scale of data ingestion and storage required.

Test Yourself: Real Deepki Questions

Three real prompts pulled from our database.

Type · system_design

Design a system to ingest, process, and store real-time energy consumption data from thousands of buildings globally. Consider data volume, latency requirements, and potential data quality issues.

Type · past_experience

Describe a project where you had to take initiative beyond your defined responsibilities to ensure its success. What motivated you, and what was the impact?

Type · coding_hard

Implement a function to calculate the carbon footprint of a building based on its energy consumption data and the carbon intensity of the local electricity grid over time. The grid carbon intensity data might be sparse.

+ many more questions, signals, and worked examples

Unlock the rubric

Deepki Interview Question Bank

A sample from our database, grouped by round. Sign up to see the full set.

9 of 14 questions shown

Recruiter Screen

1
Type · motivation
What specifically about Deepki's mission in the energy sector and our focus on decarbonization through data resonates with your career aspirations?

Coding Screen

2
Type · algorithmic
Given a stream of building energy consumption data (timestamp, sensor_id, kWh), write a function to detect anomalous spikes in energy usage for a specific building within a given time window. Assume data arrives out of order.
3
Type · algorithmic
You are given a list of sensor readings for a building, where each reading has a timestamp and a value (e.g., temperature, power). Write a function to calculate the average value for each hour of the day, ignoring readings outside of typical operating hours (e.g., 7 AM to 7 PM).
+ 1 more questions in this round (sign up to unlock)

System Design

4
Type · system_design
Design a system to ingest, process, and store real-time energy consumption data from thousands of buildings globally. Consider data volume, latency requirements, and potential data quality issues.
5
Type · system_design
Design an API for retrieving energy consumption data for a specific building over a given date range. The API should support filtering by sensor type and aggregation level (e.g., hourly, daily).
+ 1 more questions in this round (sign up to unlock)

Onsite Coding

6
Type · coding_hard
Implement a function to calculate the carbon footprint of a building based on its energy consumption data and the carbon intensity of the local electricity grid over time. The grid carbon intensity data might be sparse.
7
Type · debugging
A customer reports that their building's daily energy report shows inconsistent totals. Debug the provided Python code which aggregates hourly consumption data into daily totals. Identify and fix the bug.
+ 1 more questions in this round (sign up to unlock)

Behavioral / Leadership

8
Type · past_experience
Describe a time you had to work with a complex, poorly documented legacy system. What steps did you take to understand it, and what was the outcome?
9
Type · past_experience
Tell me about a time you disagreed with a technical decision made by your team or lead. How did you approach the situation, and what was the result?
+ 2 more questions in this round (sign up to unlock)