Mid Data Engineer, Software

Experian

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

Posted 11/6/2026full-timeRemote • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining large-scale data pipelines using Spark and cloud-native technologies, while ensuring high-quality code through testing and documentation. Proficient in collaborating within agile teams and providing technical guidance to enhance system reliability and performance.

Highest-signal resume keywords

Data Pipeline DevelopmentApache SparkCloud-Native TechnologiesGit-Based Version ControlAgile Methodologies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSoftware EngineeringParallelized Data WorkloadsFunctional ProgrammingJavaPythonRustScalaAWS Data ServicesGCP Data Services

Soft Skills

Strong Communication SkillsCollaboration

Tools & Technologies

GitHubBitbucketS3GlueAthena

Industry Keywords

Data PlatformsDistributed SystemsData Processing WorkflowsSystem ReliabilityLarge-Scale Data Ecosystems

Tech Stack

Tools & technologies

ApacheAWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaPythonRustScalaSpark

About the role

Key responsibilities & impact

Design, develop, and maintain large-scale data pipelines using 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
Ensure software quality through clean, testable, well-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 engineering best practices
Support deployments, monitoring, alerting, and continuous improvement of system reliability
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
Experience designing and operating highly parallelized data workloads
Proficiency with Git-based version control systems, such as GitHub and 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: hands-on experience with AWS, GCP, or Azure data platforms and services such as S3, Glue, and Athena
Nice to have: expertise with Scala and Apache Spark
Nice to have: experience with functional programming or Java, Python, or Rust
Nice to have: familiarity with modern data platform architectures and large-scale data ecosystems

Benefits

Comp & perks

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