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EY

Data Engineer – PySpark, Redshift, Iceberg, Airflow

EY

. Develop and maintain scalable data ingestion, transformation, and delivery pipelines .

Posted 9/15/2026full-timeSão Paulo • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and maintaining scalable data ingestion, transformation, and delivery pipelines using PySpark, Amazon Redshift, and Apache Airflow. Proficient in data governance, quality assurance, and optimizing cloud-based data platforms within complex corporate environments.

Highest-signal resume keywords
Data Engineering ExperiencePySpark ProficiencyAmazon Redshift ExpertiseApache Airflow ExperienceAdvanced SQL Skills

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Data IngestionData TransformationData Delivery PipelinesETL FrameworksELT FrameworksData Lake ArchitectureData Warehouse ArchitectureLakehouse ArchitectureData MonitoringData Governance
Soft Skills
CollaborationProblem-SolvingCommunication
Tools & Technologies
PySparkAmazon RedshiftApache IcebergApache AirflowAWS Services
Industry Keywords
Cloud Data PlatformData QualityData CatalogingTechnical DocumentationOperational Excellence

Tech Stack

Tools & technologies
AirflowAmazon RedshiftApacheAWSETLPySparkSQL

About the role

Key responsibilities & impact
  • Develop and maintain scalable data ingestion, transformation, and delivery pipelines
  • Build solutions using PySpark, Amazon Redshift, Apache Iceberg, and Apache Airflow
  • Develop and support platforms based on Lakehouse and Data Warehouse architectures
  • Implement and enhance high-performance ETL and ELT frameworks
  • Ensure data and pipeline quality, reliability, scalability, and performance
  • Monitor critical workloads and troubleshoot issues in production environments
  • Collaborate with architects, analysts, and stakeholders to develop solutions aligned with business needs
  • Contribute to data governance, quality, and cataloging initiatives
  • Participate in architecture reviews, technical design, and code reviews
  • Keep technical documentation up to date and aligned with corporate standards
  • Support the modernization and continuous evolution of the cloud data platform
  • Promote data engineering best practices and operational excellence

Requirements

What you’ll need
  • Advanced English proficiency for professional communication
  • Experience in Data Engineering
  • Solid experience developing cloud-based data platforms
  • Strong knowledge of PySpark for distributed data processing
  • Hands-on experience with Amazon Redshift
  • Solid knowledge of Apache Iceberg
  • Experience with Apache Airflow for pipeline orchestration
  • Experience with AWS services for data platforms
  • Experience building scalable data ingestion, transformation, and delivery pipelines
  • Knowledge of Data Lake, Data Warehouse, and Lakehouse architectures
  • Experience with ETL and ELT frameworks
  • Advanced SQL skills and experience optimizing analytical workloads
  • Experience with data monitoring, governance, and quality
  • Ability to work in complex corporate environments with large data volumes

Benefits

Comp & perks
  • Medical and dental insurance
  • Childcare assistance
  • EY benefits and exclusive discounts platform
  • Education incentives
  • Birthday day off
  • Gympass/Wellhub
  • Profit-sharing plan
  • Private pension plan
  • Meal and/or food and transportation allowance
  • Remote work flexibility
  • Inclusive culture and equity support programs and groups