Data Engineer, AWS

Keyrus

. Design and evolve modern, scalable, reliable, and high-performance data architectures .

Posted 10/8/2026full-timeRemote • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing scalable data architectures and pipelines, with a strong focus on data quality, governance, and integration across various platforms. Proficient in leveraging cloud technologies and advanced programming skills to support analytics and business intelligence initiatives.

Highest-signal resume keywords

DatabricksApache Spark (PySpark)Python ProgrammingAWS GlueSQL

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignETL/ELT ProcessesData ModelingData Lake ArchitecturesData Warehouse ArchitecturesBatch ProcessingNear-Real-Time IngestionData IntegrationAnalytics ProjectsComplex Problem-Solving

Soft Skills

Analytical SkillsDocumentation Skills

Tools & Technologies

AWS LambdaAmazon S3AWS IAMQlik SenseQlikViewGitCI/CD Practices

Industry Keywords

Data GovernanceData QualityBusiness IntelligenceData ArchitectureDistributed Processing

Tech Stack

Tools & technologies

ApacheAWSETLPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Design and evolve modern, scalable, reliable, and high-performance data architectures
Build and optimize data pipelines for Analytics, BI, and data-driven decision-making
Architect cloud data engineering and distributed processing solutions
Integrate different data sources and platforms, ensuring data quality, availability, and governance
Continuously improve the data platform by enhancing performance, reliability, and efficiency
Work with business and BI teams to transform requirements into sustainable data solutions
Develop and maintain scalable pipelines for corporate analytics and reporting
Build batch and near-real-time ingestion processes
Perform the transformation and processing of large volumes of data
Participate in code reviews, architecture definition, and continuous improvement initiatives
Collaborate with architects, BI teams, analysts, developers, and business stakeholders

Requirements

What you’ll need

Fluent English for daily collaboration with global teams
Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field
Strong experience with Databricks
Advanced knowledge of Apache Spark (PySpark)
Advanced Python programming skills
Experience designing and implementing data pipelines and ETL/ELT processes
Practical knowledge of AWS Glue, AWS Lambda, Amazon S3, and AWS IAM
Strong command of SQL and data modeling
Experience with modern Data Lake and Data Warehouse architectures
Experience working on Business Intelligence and Analytics projects
Experience with data integration and modeling for Qlik Sense/QlikView
Knowledge of code version control (Git) and CI/CD practices
Strong analytical and complex problem-solving skills
Ability to document processes, data models, integration flows, and operating procedures

Benefits

Comp & perks

Exposure to people from around the world
Exchange of knowledge and ideas
Diverse and multicultural environment
Opportunities for collaboration across specialties, functions, and geographies