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Updated 2026-07-04 20:00 UTC·© 2025–2026 RoleSuite
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Engenheiro de Dados AWS/Databricks

Jobgether · Brazil

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Engenheiro de Dados AWS/Databricks based in Brazil.

This role is focused on building and evolving modern data engineering solutions within a cloud-native and governance-driven architecture. You will play a key part in designing and maintaining scalable data pipelines that support ingestion, transformation, and analytics across enterprise systems. The position is centered on Databricks and AWS ecosystems, with strong emphasis on data quality, cataloging, and compliance with governance standards such as LGPD. You will work with modern frameworks and distributed data processing technologies to ensure reliable and well-structured data products. In addition, you will contribute to observability, performance, and orchestration of data workflows in both batch and streaming environments. This is a highly technical and impactful role within a collaborative and global environment focused on data excellence and innovation.

Accountabilities:

  • Build and maintain scalable data pipelines for ingestion, transformation, and data curation
  • Develop ELT/ETL workflows using PySpark and SQL within Medallion architecture (Bronze, Silver, Gold)
  • Implement data quality rules, monitoring mechanisms, and remediation standards to ensure reliable datasets
  • Perform data profiling and source system analysis to support governance and data cataloging initiatives
  • Manage dataset cataloging and enforce data policies aligned with LGPD using Unity Catalog
  • Integrate APIs, external data sources, and orchestration tools into end-to-end data workflows
  • Support both batch and streaming ingestion processes using tools such as Auto Loader, Kafka, and Structured Streaming
  • Collaborate on data modeling practices including Dimensional Modeling and Data Vault approaches
  • Ensure observability and monitoring of pipelines to guarantee performance and reliability
  • Requirements:

    • Solid experience as a Data Engineer in production environments
    • Strong hands-on experience with Databricks (Delta Lake)
    • Advanced knowledge of PySpark and SQL
    • Experience building ETL/ELT pipelines in cloud-based environments
    • Knowledge of Medallion architecture and modern data lakehouse concepts
    • Experience with batch and streaming ingestion (Kafka, Auto Loader, Structured Streaming)
    • Understanding of data modeling techniques (Dimensional Modeling, Data Vault)
    • Experience with dbt and/or Delta Live Tables (DLT)
    • Familiarity with data quality frameworks such as Great Expectations or DLT Expectations
    • Experience with pipeline orchestration tools like Databricks Workflows or Apache Airflow
    • Knowledge of APIs and multi-source data integration
    • Experience with data observability, monitoring, and troubleshooting pipelines
    • English proficiency for communication in international environments (fluency preferred)
    • Databricks certification and experience in data governance projects are a plus
    • Knowledge of LGPD and Unity Catalog implementation is a strong plus
    • Benefits:

      • Flexible employment options (CLT or PJ)
      • 100% remote work model
      • Meal or food allowance
      • Health and dental insurance coverage
      • Life insurance
      • Access to training platforms and continuous learning programs
      • Discounts on courses, universities, and language schools
      • Mentorship programs and career development support
      • Wellness and healthcare benefits through partner networks
      • Travel and lifestyle discount clubs
      • Pet care benefits and additional employee support programs.

Data & ML pay context

Based on 1,466 disclosed Data & ML salaries on RoleSuite, the role pays a median of $161K/year, with most offers between $127K and $203K (10th–90th percentile: $102K–$244K).

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