Mid Data & Software Engineer in Brazil at Jobgether

• Design, develop, and maintain large-scale data pipelines using Apache Spark and cloud-native technologies, ensuring performance, scalability, and reliability.

• Solve complex data engineering challenges by building efficient distributed systems and optimizing data processing workflows.

• Contribute to production-grade data platforms through high-quality, tested code and end-to-end feature development.

• Maintain clean, reusable, testable, and well-documented code while following engineering standards and participating in code reviews.

• Collaborate within agile value stream teams, working closely with engineers, product owners, and cross-functional stakeholders.

• Contribute to technical discussions, architecture decisions, and peer development by sharing knowledge and promoting engineering best practices.

• Support software releases and operational processes, including deployments, monitoring, alerting, and continuous reliability improvements.

• Identify and implement opportunities to improve processing performance, cost efficiency, and platform scalability.

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

• Solid professional experience in software engineering or data engineering.

• Experience designing and operating highly parallelized data workloads.

• Proficiency with Git-based version control systems such as GitHub or Bitbucket.

• Familiarity with agile methodologies and collaborative development across multiple teams.

• Strong communication skills and the ability to contribute effectively to technical discussions and support colleagues.

• Advanced English proficiency.

• Availability to travel to São Carlos, São Paulo, when required.

Nice to have:

• Hands-on experience with cloud-native data platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.

• Familiarity with cloud services such as Amazon S3, AWS Glue, and Amazon Athena, or equivalent technologies.

• Experience building and optimizing large-scale data pipelines using Scala and Apache Spark.

• Knowledge of functional programming, particularly Scala, or experience with languages such as Java, Python, or Rust.

• Familiarity with modern data platform architectures and large-scale data ecosystems.

• Opportunity to work on large-scale, cloud-native data platforms and business-critical technology solutions.

• Collaborative environment with agile teams and global stakeholders.

• Opportunities to contribute to technical architecture, engineering standards, and continuous improvement initiatives.

• Inclusive workplace culture focused on diversity, belonging, and professional development.

• Access to employee affinity groups and initiatives supporting inclusion, representation, and equal opportunity.