Mid Data & Software Engineer

Experian

. Design, develop, and maintain large-scale data pipelines using Scala, Spark, and cloud-native technologies .

Posted 11/4/2026full-timeRemote • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining large-scale data pipelines using Scala and Spark, with a strong focus on cloud-native technologies and distributed systems. Proficient in ensuring software quality through clean coding practices and collaboration in agile environments.

Highest-signal resume keywords

Scala ProgrammingApache SparkCloud-Native TechnologiesDistributed SystemsData Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData Processing WorkflowsSoftware Quality AssuranceData Workload OptimizationVersion Control (Git)Data PartitioningParallel ProgrammingFunctional ProgrammingData Transformation Frameworks (DBT)Agile Methodologies

Soft Skills

Strong Communication SkillsCollaborationTechnical Guidance

Tools & Technologies

AWSGCPAzureS3GlueAthenaGitHubBitbucket

Industry Keywords

Data EngineeringCloud ComputingDistributed SystemsData EcosystemsSoftware Development

Tech Stack

Tools & technologies

ApacheAWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaPythonRustScalaSpark

About the role

Key responsibilities & impact

Design, develop, and maintain large-scale data pipelines using Scala, Spark, and cloud-native technologies
Solve complex data engineering challenges through efficient, resilient distributed systems and optimized data processing workflows
Contribute to production-grade data platforms with high-quality, tested code and end-to-end feature development
Ensure software quality through clean, testable, documented code, code reviews, and engineering standards
Collaborate with engineers, product owners, and cross-functional stakeholders in agile value stream teams
Provide technical guidance through architecture discussions, code reviews, and promotion of engineering best practices
Support releases and operations, including deployments, monitoring, alerting, and reliability improvements
Improve performance, cost efficiency, and scalability of data processing workloads

Requirements

What you’ll need

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 such as AWS, GCP, or Azure, including 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 such as GitHub or Bitbucket
Familiarity with agile methodologies and collaborative development in multi-team environments
Strong communication skills for technical discussions and peer development
Advanced English proficiency
Availability to travel to São Carlos/SP when needed
Nice to have: experience with DBT or other data transformation frameworks
Nice to have: knowledge of concurrent and parallel programming patterns
Nice to have: expertise in large-scale data pipelines using Scala and Apache Spark
Nice to have: experience with functional programming (Scala) or Java, Python, or Rust
Nice to have: familiarity with modern data platform architectures and large-scale data ecosystems

Benefits

Comp & perks

Remote work options
Inclusive recruitment and professional development initiatives
Affinity groups supporting underrepresented groups: ExperianPride, Ubuntu, Women in Experian, Aspire, and Connecting Generations