What is a Data Analyst at Repsol?

A Data Analyst at Repsol is a pivotal link between raw energy data and strategic business decisions. As the company continues its digital transformation and leads the energy transition, data has become the primary fuel for optimizing operations. In this role, you aren't just processing numbers; you are interpreting complex market signals to influence how one of the world's largest energy providers delivers value to millions of customers.

The impact of this position is felt across the entire value chain, from refining and chemicals to retail and renewable energy. For example, within the Pricing Area, Data Analysts develop insights that affect fuel pricing at thousands of service stations nationwide. Your work directly contributes to Repsol’s competitiveness in a volatile global market, ensuring that the company remains agile and data-driven in its pursuit of sustainable energy solutions.

Working at Repsol offers a unique blend of scale and complexity. You will tackle high-impact problems, such as predicting consumer behavior, optimizing supply chains, or enhancing the digital experience for users of the Waylet app. This role requires a professional who can navigate large-scale datasets while maintaining a sharp focus on the business implications of their findings.

Common Interview Questions

Expect a mix of technical tests and behavioral questions. The goal is to see how you think and how you apply your skills to Repsol's specific business context.

Technical and SQL Questions

These questions test your ability to handle data efficiently and accurately.

• Explain the difference between a WHERE clause and a HAVING clause.
• How do you handle a many-to-many relationship in a data model?
• Write a query to find the second-highest sales figure for a given day.
• What are window functions, and when would you use them instead of a GROUP BY?
• How would you optimize a query that is running slowly on a large dataset?

Business Intelligence and Case Studies

These evaluate your ability to apply data to business problems.

• Describe a time you turned a complex dataset into an actionable business insight.
• What KPIs would you track to measure the success of a new loyalty app?
• How would you design a dashboard for a regional manager who only has 5 minutes to look at it?
• If two data sources show conflicting results for the same metric, how do you investigate?

Behavioral and Leadership

Repsol looks for candidates who align with their collaborative and safety-conscious culture.

• Tell me about a time you had to explain a technical finding to a stakeholder who didn't understand data.
• Describe a situation where you had to work with someone who had a different perspective than yours.
• How do you prioritize your tasks when you have multiple urgent requests from different departments?
• Give an example of a mistake you made in an analysis and how you corrected it.

Getting Ready for Your Interviews

Preparation for a Data Analyst role at Repsol requires a dual focus on technical proficiency and business intuition. You should approach the process as a consultant would: identifying the problem, structuring a data-driven solution, and communicating the "so what" to stakeholders.

Role-related knowledge – You must demonstrate a high level of comfort with SQL and data visualization tools like Power BI. Interviewers look for your ability to clean, manipulate, and interpret data to answer specific business questions, particularly those related to pricing or retail performance.

Problem-solving ability – Repsol values candidates who can break down complex, ambiguous challenges into manageable analytical tasks. You will be evaluated on how you structure your thoughts and whether you can account for external variables, such as market volatility or regulatory changes.

Business Acumen – Beyond the code, you need to show an understanding of the energy sector. Demonstrating knowledge of how Repsol generates revenue and the specific challenges of the energy transition will set you apart from purely technical candidates.

Culture fit and Values – Collaboration and safety are core to Repsol’s DNA. You should be prepared to discuss how you work within multidisciplinary teams and how you handle feedback or shifting priorities in a large corporate environment.

Interview Process Overview

The interview process at Repsol is designed to evaluate both your technical depth and your ability to thrive in a corporate environment. It typically begins with a screening call from the talent acquisition team to discuss your background and interest in the energy sector. Following this, you will move into more specialized rounds that focus on your analytical capabilities.

Candidates can expect a mix of remote interviews and potentially in-person sessions if applying for roles in major hubs like Madrid. The process is known for being thorough, often involving managers from the specific business unit (such as Pricing or Business Intelligence) to ensure you have the functional knowledge required for the day-to-day work. While the rigor is high, the tone is generally professional and focused on finding a long-term fit for the team.

The timeline above illustrates the standard progression from initial contact to the final decision. Candidates should use this to pace their preparation, focusing heavily on technical fundamentals in the early stages and shifting toward business case studies and cultural alignment as they approach the final rounds. Note that the duration between stages can vary depending on the specific business unit's urgency.

Deep Dive into Evaluation Areas

SQL and Data Manipulation

Technical proficiency is a non-negotiable requirement for Data Analysts. You will be tested on your ability to extract insights from relational databases efficiently. The focus is often on real-world scenarios, such as analyzing sales trends or customer behavior over time.

Be ready to go over:

• Complex Joins and Aggregations – Understanding the nuances of different join types and how to summarize data across multiple dimensions.
• Window Functions – Using functions like RANK, LEAD, and LAG to perform time-series analysis or comparative reporting.
• Data Cleaning – Handling null values, duplicates, and inconsistent data formats within a query.

Example questions or scenarios:

• "Write a query to find the top three performing service stations in each region based on monthly revenue."
• "How would you identify customers who haven't made a purchase in the last 30 days but were previously active?"

Business Intelligence and Visualization

At Repsol, data is only as good as the decisions it enables. You must demonstrate that you can translate complex data into clear, actionable dashboards that executives and managers can use to steer the business.

Be ready to go over:

• Power BI and DAX – Creating calculated measures and columns to drive dynamic reporting.
• Data Storytelling – Choosing the right visualization type for the specific insight you are trying to convey.
• User-Centric Design – Ensuring that dashboards are intuitive for non-technical business users.

Advanced concepts (less common):

• Integration with Azure data lakes.
• Row-level security (RLS) implementation in reports.
• Automating report refreshes and data flows.

Pricing and Business Logic

For roles within the Pricing Area, you will face questions that test your logic and mathematical intuition. Repsol operates in a highly competitive market where small changes in pricing can have national impacts.

Be ready to go over:

• Elasticity and Demand – How changes in price affect volume and total margin.
• Competitor Analysis – Structuring a framework to monitor and react to market competitors.
• Impact Assessment – Measuring the success of a pricing strategy or a promotional campaign.

Example questions or scenarios:

• "If we increase the price of premium fuel by 2%, how would you estimate the impact on total volume and customer loyalty?"
• "Walk us through how you would design a dashboard to track the pricing performance of a new product launch."

Key Responsibilities

As a Data Analyst at Repsol, your primary responsibility is to transform data into a strategic asset. You will spend a significant portion of your time collaborating with business stakeholders to understand their pain points and translating those into analytical requirements. Whether you are working in Madrid on national pricing strategies or supporting a specific business unit, your deliverables will include automated reports, ad-hoc analyses, and data-driven recommendations.

You will act as a bridge between the technical infrastructure (IT and Data Engineering) and the functional teams. This involves ensuring data quality, maintaining documentation for your analytical models, and constantly looking for ways to improve existing processes. Typical projects might include optimizing the supply chain for lubricants, analyzing the effectiveness of loyalty programs, or developing predictive models for energy demand.

Collaboration is a daily requirement. You will work closely with Product Managers to define KPIs, with Data Engineers to ensure your pipelines are robust, and with Business Leads to present your findings. The role is dynamic, requiring you to pivot between deep technical work and high-level strategic communication.

Role Requirements & Qualifications

To be competitive for a Data Analyst position at Repsol, you should possess a blend of technical expertise and professional experience.

• Technical Skills – High proficiency in SQL is essential. Experience with Python or R for statistical analysis is highly valued. You should be an expert in Power BI or similar BI tools (Tableau, Qlik).
• Experience Level – Typically, 2–5 years of experience in data analysis, business intelligence, or a related field is required. Experience in the energy, retail, or consulting sectors is a significant advantage.
• Education – A degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, or Computer Science.
• Soft Skills – Excellent communication skills in both Spanish and English are often required, especially for roles with international visibility. You must be able to explain technical concepts to a non-technical audience.

Must-have skills:

• Advanced SQL and relational database knowledge.
• Mastery of Power BI for corporate reporting.
• Strong analytical mindset and attention to detail.

Nice-to-have skills:

• Knowledge of Cloud platforms (Azure preferred).
• Experience with Big Data technologies (Spark, Databricks).
• Background in financial modeling or pricing optimization.

Frequently Asked Questions

Q: How difficult is the interview process for a Data Analyst? The difficulty is generally rated as average to high. While the technical requirements are standard for the industry, the emphasis on business logic and the specific complexities of the energy sector add an extra layer of challenge.

Q: What is the typical timeline from application to offer? At Repsol, the process can be slower than at a tech startup, often taking 4 to 8 weeks. This is due to the multiple layers of approval required in a large, established corporation.

Q: Does Repsol offer remote work for Data Analysts? Repsol has embraced hybrid work models, especially for digital and analytical roles based in Madrid. However, specific expectations depend on the team and the nature of the projects you are supporting.

Q: What makes a candidate stand out at Repsol? Candidates who demonstrate a genuine interest in the energy industry and who can speak confidently about "the business behind the data" usually perform best. Showing that you are a proactive problem-solver rather than just a "ticket-taker" is key.

Other General Tips

• Understand the Energy Context: Before your interview, research Repsol’s recent announcements regarding green hydrogen, renewable energy, and their goal to be net-zero by 2050. This shows commitment.
• Focus on Impact: When discussing your past projects, always mention the business outcome. Did you save money? Increase efficiency? Improve customer satisfaction?
• Master the Tools: Since Power BI is a staple at Repsol, ensure you are comfortable discussing DAX and data modeling best practices.
• Prepare for Spanish and English: Depending on the team, the interview may switch between languages to test your fluency, especially for roles with global impact.

Summary & Next Steps

Becoming a Data Analyst at Repsol is an opportunity to work at the intersection of traditional industry and cutting-edge digital innovation. The role offers the chance to influence national-scale operations and contribute to a sustainable energy future. By mastering the technical fundamentals and aligning your problem-solving approach with Repsol’s strategic goals, you can position yourself as a top-tier candidate.

Your preparation should focus on demonstrating how you can provide clarity in a complex environment. Use the resources available on Dataford to sharpen your SQL skills and practice business case studies. With a structured approach and a clear understanding of the company's values, you are well-equipped to succeed in this process.

The salary data provided reflects the competitive compensation packages Repsol offers to attract top analytical talent. When reviewing these figures, consider the total rewards package, which often includes performance bonuses, health insurance, and professional development opportunities. Seniority and location—particularly in high-cost areas like Madrid—will also influence the final offer.