Senior Data Software Engineer

Accountabilities:: Design, develop, and maintain scalable data pipelines that enable reliable data movement across multiple systems. Build and manage data ingestion processes from a variety of source systems. Write clean, efficient, maintainable, and well-tested code in accordance with established software engineering practices. Collaborate with cross-functional teams to understand data requirements and translate them into effective technical solutions. Monitor data pipeline performance and proactively identify and resolve issues to maintain system reliability. Participate in code reviews, uphold engineering quality standards, and share technical knowledge with colleagues. Troubleshoot data quality issues and ensure accuracy, consistency, and reliability across datasets. Contribute to the continuous improvement of data architecture, engineering practices, and development standards. Document technical processes, solutions, and workflows to support knowledge sharing and team onboarding. Participate in agile development activities, including sprint planning and other team ceremonies. Requirements: At least 3 years of relevant professional experience in data engineering or a related software engineering field. Strong hands-on experience with PySpark and Spark SQL for building and processing large-scale data workflows. Experience building and managing Lakeflow pipelines and Jobs for data orchestration. Proficiency with Auto Loader and JDBC/CDC ingestion methods , working with source systems such as DB2 and SQL Server. Solid experience with Delta Lake and Unity Catalog for data storage, management, and governance. Background in data quality assurance and source reconciliation to maintain accurate and trustworthy datasets. Experience writing unit tests using pytest to validate code reliability and correctness. Working knowledge of Git and Asset Bundles for version control and deployment management. English proficiency at B2 level or higher , with the ability to collaborate effectively in an international working environment. Strong problem-solving skills, attention to detail, and a commitment to clean, reliable, and maintainable code. Ability to collaborate with cross-functional teams, communicate technical concepts clearly, and contribute to shared engineering goals. Nice to have: Experience with DataStage migration projects. Background in data extraction from Dynamics 365/Dataverse. Databricks certification. Benefits: Opportunity to work on international projects for leading global brands. Collaboration with diverse, highly skilled teams across different locations. Healthcare benefits. Employee financial programs. Paid time off and sick leave. Professional development opportunities, including upskilling, reskilling, and certification courses. Unlimited access to LinkedIn Learning, with a library of more than 22,000 courses. Global career development opportunities. Opportunities to participate in volunteering initiatives and community activities. Employee groups that support connection and collaboration across the organization. Opportunity to join an award-winning workplace culture recognized by Glassdoor, Newsweek, and LinkedIn. Remote working opportunity; specific working hours and Brazil-specific employment conditions were not detailed in the source description.