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Engenheiro de Dados GCP - Sênior

jobgether · Brazil

Senior LevelRemoteExternal listingfull-time20 days ago

About The Role

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Engenheiro de Dados GCP - Sênior based in Brazil.**

This role is designed for a senior data engineering professional focused on modernizing and optimizing large-scale data platforms in Google Cloud environments.

You will work on complex data transformation initiatives, migrating legacy pipelines into scalable cloud-native architectures.

The position combines advanced SQL development, Python/PySpark engineering, automation, and cloud data solutions.

You will contribute to improving data reliability, performance, and governance across high-volume environments.

The role requires strong technical expertise, problem-solving abilities, and experience working with modern data ecosystems.

You will collaborate with technical teams to deliver efficient, secure, and scalable data solutions that generate business value.

### Accountabilities

As a Senior Data Engineer, you will be responsible for designing, modernizing, and optimizing data pipelines while ensuring data quality, scalability, and operational efficiency.

  • Reverse engineer complex PySpark-based data logic and translate it into optimized native SQL solutions within BigQuery.
  • Use AI-powered tools to accelerate data pipeline conversion, improve productivity, and automate validation processes.
  • Modernize and develop data ingestion workflows by replacing legacy tools with native Google Cloud services such as Datastream, Dataflow, and Cloud Run.
  • Build and manage data orchestration workflows using Cloud Composer (Apache Airflow).
  • Manage and optimize data stored in Apache Iceberg format through BigLake, ensuring performance, scalability, and cost efficiency.
  • Design and execute automated testing frameworks to validate data migration accuracy and business logic consistency.
  • Perform data reconciliation activities, including row count validation, partition verification, business key comparisons, checksums, and hash validations.
  • Validate key business aggregations through accuracy checks involving totals, distinct counts, minimums, and maximums.
  • Troubleshoot complex data performance issues, schema evolution challenges, and large-scale data processing scenarios.
  • Collaborate with technical stakeholders to ensure successful delivery of cloud data transformation initiatives.

## Requirements

The ideal candidate should have strong experience in cloud data engineering, advanced SQL development, and modern data architecture, with the ability to handle complex, high-volume data environments.

  • Minimum 6 years of professional experience working with Google Cloud Platform, especially BigQuery, Google Cloud Storage (GCS), and Cloud Composer (Airflow).
  • Strong expertise in advanced SQL and Python/PySpark development.
  • Proven experience designing, developing, and optimizing large-scale data pipelines.
  • Hands-on experience with open table formats, especially Apache Iceberg and Delta, including conversion and data management.
  • Experience with data transformation orchestration tools such as Dataform or dbt.
  • Strong understanding of cloud-native data services and migration strategies.
  • Ability to solve complex performance, scalability, and schema evolution challenges in Terabyte-scale environments.
  • Analytical mindset with strong problem-solving skills and attention to data quality.
  • Ability to work independently in remote environments while collaborating effectively with technical teams.

## Benefits

  • Fully remote work model.
  • Opportunity to work on challenging cloud data modernization projects.
  • Temporary project contract with an expected duration of up to 4 months, with potential continuation.
  • Exposure to modern Google Cloud technologies, AI-assisted engineering practices, and large-scale data platforms.
  • Opportunity to collaborate with experienced professionals in data, cloud, and artificial intelligence environments.
  • Continuous learning and professional development opportunities.
  • Inclusive environment open to professionals with diverse backgrounds.

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