Mid Data & Software Engineer

Experian is a global data and technology company that powers opportunities for people and businesses around the world. We operate across a wide range of markets, including financial services, healthcare, automotive, agribusiness, insurance, among others. Experian invests in people and in advanced new technologies to unlock the power of data. We have an incredible team of 25,200 employees across 32 countries. Our uniqueness is valuing yours. Experian’s people-centric, inclusive, and purpose-driven culture has been recognized with several awards — including World’s Best Workplaces™ 2025 (Fortune Global Top 25) and Great Place To Work™ in 26 countries, among others. Check out Experian Life on social media or explore our careers site to understand why. Experian is also proud to be an equal opportunity and affirmative action employer. We are looking for a Software Engineer to design, build, and evolve highly scalable and resilient data platform solutions that power Experian Marketing Services’ core products. In this role, you will work on large-scale, cloud-native data pipelines, optimize distributed processing systems, and ensure the reliability and performance of petabyte-scale workloads. You will operate within agile value stream teams, applying strong engineering practices and collaborating with global stakeholders to deliver high-quality, business-critical data solutions. Your key responsibilities - Design, develop, and maintain large-scale data pipelines using Scala, Spark, and cloud-native technologies, ensuring high performance, scalability, and reliability. - Solve complex data engineering challenges by designing efficient, resilient distributed systems and optimizing data processing workflows. - Contribute to production-grade data platforms, delivering high-quality, tested code and supporting end-to-end feature development. - Ensure software quality through clean, testable, and well-documented code, code reviews, and adherence to engineering standards. - Collaborate within agile value stream teams, working closely with engineers, product owners, and cross-functional stakeholders to deliver aligned technical solutions. - Provide technical guidance to peers, contributing to architecture discussions, code reviews, and promoting best engineering practices.

- Support release and operational processes, including deployments, monitoring, alerting, and continuous improvement of system reliability. - Drive improvements in performance, cost efficiency, and scalability of data processing workloads. What we expect from you - Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. - Solid experience in software or data engineering. - Hands-on experience with cloud-native data platforms (AWS, GCP, or Azure), including services such as S3, Glue, Athena, or equivalent. - Strong understanding of distributed systems, resiliency patterns, data partitioning, and efficient data access strategies. - Experience designing and operating highly parallelized data workloads. - Proficiency with Git-based version control systems (GitHub, Bitbucket, etc. ). - Familiarity with agile methodologies and collaborative development in multi-team environments. - Strong communication skills, with the ability to contribute in technical discussions and support peer development. - Advanced English proficiency and availability to travel to São Carlos/SP when needed. Nice to have - Experience with DBT or other data transformation frameworks. - Knowledge of concurrent and parallel programming patterns. - Expertise in building and optimizing large-scale data pipelines using Scala and Apache Spark. - Experience with functional programming (Scala) or languages such as Java, Python, or Rust. - Familiarity with modern data platform architectures and large-scale data ecosystems.