Engenheiro(a)deDadoseBackendSênior(PJ)

## Accountabilities Design, develop, and evolve data pipelines that support eligibility, selection, and purchase processes for receivables, ensuring accuracy and efficiency in data processing. Implement and maintain business rules related to credit assignment and structured financial operations, translating complex requirements into robust system logic. Build and support data validation, transformation, and calculation processes for financial indicators and operational metrics. Develop and maintain integrations between data pipelines and backend services, ensuring consistency and reliability across systems. Contribute to the evolution of distributed and event-driven architectures, supporting scalable and resilient data flows. Investigate and resolve complex issues in large-scale data processing environments, ensuring system stability and performance. Participate in technical reviews, promoting engineering best practices, code quality, and architectural improvements. Collaborate with cross-functional teams to design solutions that automate business decisions and improve operational efficiency. Requirements: Solid experience with Python for backend development and data pipeline construction. Strong experience with large-scale data processing frameworks such as Apache Spark, Databricks, or similar technologies. Advanced knowledge of data modeling, ETL/ELT processes, and data transformation workflows. Experience with messaging systems and event streaming tools such as Kafka or equivalent. Strong experience building and consuming REST APIs and integrating backend services. Proficiency in Git and collaborative software development practices. Advanced SQL skills for data manipulation, analysis, and optimization. Experience with distributed and event-driven architectures in production environments. Hands-on experience integrating data pipelines with backend systems. Familiarity with cloud environments such as AWS or similar platforms. Experience with data pipeline orchestra