Data Engineer + Java/Kafka

Develop and maintain data engineering solutions and backend services on the bank's analytical platform, contributing to ensuring that common customer information and other critical data assets are built and exposed with quality, robustness, scalability, and operational efficiency for consumption by other areas and applications of the bank. Analyze functional and non-functional requirements, understand business needs, and contribute to transforming them into viable and maintainable technical solutions. Implement ETL/ELT processes on Azure Databricks to build and maintain the common data layer, with attention to the consistency, traceability, and reliability of the information. Develop software components and REST APIs to expose data and capabilities to operational systems, following well-defined contracts and team standards. Implement assigned functionalities, participate in diagnosing production problems, and collaborate in root cause analysis and technical incident resolution. Apply software quality standards established by the team, including coding best practices, testing, code review, and CI/CD. Contribute to the performance and efficiency optimization of the developed solutions, paying attention to batch execution times, resource consumption, and Spark/Databricks performance. Use AI tools applied to development as productivity accelerators and support for analysis, implementation, and troubleshooting, maintaining technical judgment and validation over the results. Collaborate effectively with the technical team and other areas, communicating progress, dependencies, doubts, and improvement proposals. Maintain a continuous learning attitude, exploring new technologies, patterns, and ways of working that improve productivity and the quality of the delivered solutions.