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.