Senior Data Engineer

XTB is a global company in the financial industry focusing on online trading of financial instruments. It is the largest FinTech in Poland and a leader in Central and Eastern Europe, operating in several countries including Asia and South America. The company offers various training and development programs and is certified as a Great Place to Work.

• Several years of professional experience in Data Engineering, Analytics Engineering or a similar technical role.
• Strong practical knowledge of SQL, including working with complex transformations and large datasets.
• Good knowledge of Python for data processing, automation and integration.
• Experience designing and maintaining ETL/ELT pipelines in production environments.
• Experience with modern cloud data warehouses.
• Good understanding of data modelling, data quality and data governance principles.
• Experience with version control, testing and software engineering practices applied to data solutions.
• Ability to independently analyse complex problems and design pragmatic, maintainable solutions.
• Strong communication skills and the ability to work effectively with both technical teams and business experts.
• Good command of English.

• Design, build and maintain robust and scalable data pipelines supporting risk management and regulatory reporting processes across the XTB Group.
• Develop and optimise data models and datasets used for financial risk, capital adequacy, enterprise risk management and regulatory reporting.
• Integrate data from multiple internal systems and ensure its consistent transformation and availability within the data platform.
• Build automated data quality controls, reconciliation mechanisms and monitoring to ensure completeness, accuracy and timeliness of risk data.
• Develop solutions that reduce manual processes and increase the level of automation within the Risk Control Department.
• Work with large datasets covering trading activity, client exposures, financial instruments, market data and regulatory information.
• Cooperate with risk specialists and quantitative analysts to translate business and regulatory requirements into effective technical solutions.
• Support the development of the Risk data architecture, including solutions based on DataBricks and modern data engineering practices.
• Identify performance bottlenecks and continuously improve the reliability, maintainability and efficiency of existing data processes.
• Contribute to engineering standards, code reviews and technical design decisions within the team.