Other roles at Repsol:Software Engineer Supply Chain

Enterprise · Software Engineer Interview Guide

Interview language: Spanish

How to Pass the Repsol Software Engineer Interview in 2026

The Repsol DNA (TL;DR)

Repsol assesses technical depth and strategic thinking, particularly how candidates apply engineering principles to optimize energy production and distribution. They look for individuals who can articulate trade-offs in system design, similar to how they balance efficiency and sustainability in their operations.

The Repsol Interview Loop

Your onsite loop will typically consist of 4 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 Repsol interview outcomes, avoid these common traps:

Describing a situation where they were simply insubordinate or unwilling to compromise.
Choosing an inefficient max-flow algorithm (e.g., Ford-Fulkerson without Edmonds-Karp or Dinic's optimization).
Not addressing data ingestion challenges at scale (high volume, velocity).
Not considering the complexity of real-world logistics, such as varying transport modes, delivery windows, and dynamic demand.

Test Yourself: Real Repsol Questions

Three real prompts pulled from our database.

Type · Algorithmic

Implement a function to simulate the flow of crude oil through a network of pipelines. The function should take a graph representing the pipeline network and calculate the maximum flow from a source (e.g., extraction point) to a sink (e.g., refinery).

Type · System Design

Design a platform for analyzing seismic data to identify potential oil and gas reserves. The system needs to handle large datasets, perform complex computations (e.g., seismic imaging), and provide visualization tools for geoscientists.

Type · Behavioral

Tell me about a time you disagreed with a technical decision made by your team or manager. How did you handle the situation, and what was the result?

+ many more questions, signals, and worked examples

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Repsol Interview Question Bank

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

9 of 15 questions shown

Recruiter Screen

1
Type · Motivation
Why are you interested in joining Repsol, and what aspects of our work in the energy sector particularly appeal to you as a software engineer?

Coding Screen

2
Type · Algorithmic
Given a stream of sensor readings from oil rigs, design an algorithm to detect anomalies that could indicate equipment failure or environmental hazards. Assume readings are time-series data with multiple parameters (temperature, pressure, vibration).
3
Type · Algorithmic
You need to optimize the routing of maintenance drones across multiple offshore platforms. Given a set of platforms, their locations, and estimated travel times between them, find the shortest path that visits each platform exactly once and returns to the origin. This is a variation of the Traveling Salesperson Problem (TSP).
+ 1 more questions in this round (sign up to unlock)

System Design

4
Type · System Design
Design a real-time monitoring system for Repsol's renewable energy assets (e.g., wind farms, solar parks). The system should ingest data from thousands of sensors, process it, detect potential issues, and provide alerts to operations teams.
5
Type · System Design
Design a system to manage and optimize the supply chain logistics for refined petroleum products, from refineries to distribution terminals and retail stations. Consider inventory management, demand forecasting, and dynamic routing.
+ 1 more questions in this round (sign up to unlock)

Onsite Coding

6
Type · Coding
Write a function that takes a list of historical energy consumption data points (timestamp, consumption) for a region and identifies the top N recurring daily/weekly patterns. For example, identify peak hours or days with consistently high usage.
7
Type · Debugging
Here is a piece of code intended to calculate carbon emissions based on fuel type and quantity. It has several bugs. Find and fix them, and explain your reasoning.
+ 1 more questions in this round (sign up to unlock)

Behavioral / Leadership

8
Type · Behavioral
Tell me about a time you had to work with a complex, legacy system. What were the challenges, and how did you approach understanding and improving it?
9
Type · Behavioral
Describe a challenging technical problem you encountered on a project related to energy infrastructure or operations. How did you debug it, and what was the outcome?
+ 3 more questions in this round (sign up to unlock)

Unlock all 15 Repsol questions, free

No credit card. Every question with its framework, the grading signals interviewers score against, and a worked answer for each.

Unlock all 15 Repsol questions

Interview tracks at Repsol

How Repsol's DNA translates across functions. Pick your role.

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Practice Repsol interviews end-to-end

Repsol Mock Interview

Run a live mock interview with our AI interviewer using Repsol-style prompts. Get scored on structure, signal, and answer length - exactly how the real loop grades you.

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STAR Stories for Repsol Behavioral Rounds

Build a Story Bank of your past wins, mapped to the leadership signals Repsol interviewers grade on. Reuse them across every behavioral round.

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Repsol Interview Prep Hub

The frameworks behind every Repsol round: CIRCLES for product sense, hypothesis-driven debugging for analytical, STAR for behavioral. Learn each one in 10 minutes.

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Interview Frameworks

CIRCLES, STAR, AARRR, RICE, MECE. The exact frameworks that make Repsol interviewers nod instead of frown. Step-by-step playbooks with the moves and the pitfalls.

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Sample answers

What a strong answer to these Repsol interview questions shows.

A strong answer shows: Knowledge of max-flow algorithms.; Proficiency in graph data structures and algorithms.; Ability to model a real-world problem using graph theory..

A strong answer shows: Experience with Big Data technologies.; Understanding of parallel and distributed computing.; Knowledge of scientific computing or data processing pipelines.; Consideration of data storage and retrieval efficiency..

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