Data Analyst for Finance – Automotive Sector

Data Analyst for Finance – Automotive Sector

Role overview :

Are you passionate about transforming data into high-impact financial decisions? Do you enjoy turning complex datasets into clear, actionable insights? We are looking for a Data Analyst to support our Finance team by improving data-driven decision-making through Power BI , SQL , and Python .

Key Responsibilities :

• Design and maintain interactive dashboards in Power BI to monitor key financial KPIs (e.g., cost analysis, profitability, forecasting).
• Automate recurring financial reports using Python scripts and SQL queries from internal databases.
• Analyze large volumes of financial data to detect trends, anomalies, and optimization opportunities.
• Support the creation of forecasting models and financial simulations.
• Collaborate with Finance and Controlling teams to identify business needs and translate them into data solutions.
• Assist in internal and external audits by providing accurate, structured, and well-documented data.

Requirements :

• Minimum +2 years of experience as a data analyst, preferably in finance, controlling, taxation, or audit environments.
• Strong proficiency in Power BI , including dashboard creation, data modeling, and DAX.
• Solid experience in SQL for working with relational databases and optimizing queries.
• Working knowledge of Python for data analysis (pandas, numpy, matplotlib, etc.).
• Understanding of key financial concepts : financial statements, cost structure, CAPEX / OPEX, budget variances.
• Ability to present complex financial information in a clear, business-oriented way.
• Proactive, detail-oriented, and process improvement mindset.
• English level : C1 or higher (written and spoken). Fluent in Spanish.

Nice to have :

• Exposure to financial or Controlling sector
• Experience working in cross-functional teams.

What we offer :

• A key role within a finance team committed to digital transformation.
• A collaborative and international environment.
• Continuous learning opportunities in analytics and finance.
• Hybrid working model and flexible working hours.
• Competitive compensation and corporate benefits.