Are you passionate about data, technology, and creating meaningful impact? Join our Analytics Transformation team and help shape the future of data and analytics. We play a critical role in driving technological transformation and aligning enterprise-wide data and analytics initiatives. As part of the team, you’ll help design and evolve our data infrastructure, support the transition to a cloud-based analytics ecosystem, and actively contribute to establishing and continuously developing the environment. We work closely with stakeholders in Spain, Switzerland, and the UK to ensure high-quality, reliable financial data is available for reporting, analytics, and informed decision-making.

What You Will Do

• Partner with business stakeholders to translate requirements into technical solutions
• Design, build, and maintain data pipelines and prototypes to analyze large-volume transactional data
• Develop and optimize solutions using Databricks, PySpark, Python, SQL, and Azure Data Factory
• Ensure data quality, accuracy, and consistency of financial data
• Troubleshoot data issues end-to-end and identify root causes
• Collaborate with IT, architects, and analysts to align with platform standards
• Document data flows and support continuous improvement of data processes
• Develop and enhance a central cloud data model enabling standardized, cross country analytics

What You Bring

• Degree in Computer Science, Engineering, Business Informatics, or a related field with a strong interest for finance, data and technology
• Strong experience as a Data Engineer in a business-facing role
• Strong experience working with Databricks, Azure, Python, PySpark, and ADF
• Experience working with financial data and data quality controls
• Ability to translate ambiguous requirements into practical solutions
• Strong problem-solving, communication, and collaboration skills
• Familiarity with CI/CD and a detail-oriented, ownership-driven mindset
• Professional fluency in English and Spanish
• Experience applying AI/ML pragmatically to enhance data quality, detect anomalies, or support advanced analytics is beneficial