Top Data Engineer Jobs in Brazil

Lead data engineering efforts to build scalable ETL processes and data lakes, ensuring data integrity and supporting BI and analytics across teams.

Lead data engineering efforts to build scalable ETL pipelines and data infrastructure, ensuring data quality and supporting BI and analytics teams.

Lead data engineering efforts, building scalable ETL and data lake processes, and ensuring analytics infrastructure supports strategic growth through reliable data access.

Lead scalable data engineering efforts to deliver reliable data for cross-functional teams, optimizing ETL processes and supporting analytics and BI infrastructure.

Lead data engineering efforts, managing scalable ETL pipelines and data lake infrastructure to support business intelligence and analytics, ensuring data quality and collaboration across teams.

Lead data engineering efforts to build and manage ETL pipelines, ensure data quality, and support BI and analytics teams, enhancing strategic growth.

Lead data engineering efforts, focusing on scalable ETL pipelines and data infrastructure to support analytics and business intelligence for strategic growth.

Lead data engineering efforts, building scalable ETL and data lake processes. Collaborate with teams to ensure timely, reliable data supports business growth and analytics.

Lead scalable data engineering efforts to ensure actionable data drives strategic growth, while optimizing ETL processes and supporting analytics teams.

Lead scalable data engineering efforts, build efficient ETL and data lake processes, and collaborate with BI and Analytics to deliver actionable data.

Lead data engineering efforts to build scalable ETL pipelines and data lakes, optimize data processes, and ensure data integrity for analytics and BI support.

Lead the development of scalable data engineering initiatives, optimize ETL and data lake processes, and ensure data integrity for strategic growth at Launch Potato.

Lead data engineering efforts to build and optimize ETL and data lake processes, ensuring reliable data for analytics and BI across teams.

The Senior Data Engineer will lead scalable data efforts, optimize ETL processes, and support BI through clean dataset delivery, ensuring data integrity and impacting strategic growth.

Lead data engineering efforts to optimize ETL pipelines and data lake processes, supporting cross-functional teams with actionable insights and reliable data.

The Senior Data Engineer will design data integration systems, manage data pipelines, and ensure data architecture meets complex business needs while utilizing cloud-native solutions and AI tools.

Design and optimize ETL processes, build data pipelines with Python, manage Azure solutions, and ensure data integrity for analytics and AI initiatives.

Lead the development of an AI-powered web application that integrates data insights, mentors junior developers, and ensures high-quality delivery.

As a Staff Data Engineer, you'll design and implement governance frameworks, optimize data costs, build reusable templates, and ensure data quality and compliance using GCP.

Design and maintain data pipelines, collaborate with stakeholders, ensure data quality, deploy infrastructure as code, and optimize reporting solutions.

The Senior Data Engineer will design, implement, and optimize data pipelines and processes, ensuring data access and quality across systems while collaborating with backend and analytics teams.

Lead the design and development of scalable data acquisition systems, architect platform components, and provide technical leadership while ensuring data integrity and high performance.

Design, build, and maintain scalable data models and pipelines to ingest, transform, and ensure quality of multi-format partner data for analytics, recommendations, and product teams.

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.