Top Data Engineer Jobs in Brazil

The Software Engineer will manage data collection for model training, extending the ingestion pipeline on GCP, and collaborate on dataset roadmaps with AI teams.

The role involves sourcing audio data, managing cloud infrastructure, and collaborating on dataset development for AI model training.

The FBS AWS Engineer leads design and implementation of data products, optimizing data for reporting, and developing data pipelines, ensuring data readiness for analytical uses.

Designs, builds, and maintains scalable batch and streaming data pipelines, APIs and integrations; prepares and cleanses data; creates data models, reporting, dashboards, and access methods; applies NLP and AI/ML techniques; follows data governance; estimates and plans work for agile sprints with limited supervision.

As a Senior Backend Software Engineer, you'll design scalable data pipelines and cloud solutions, ensuring data quality and governance while mentoring engineers and collaborating on cross-functional projects.

The role involves designing and implementing scalable applications, building backend services, developing ETL processes, and database management using Python and various technologies.

As a Machine Learning Engineer/Data Scientist, you'll build and deploy ML solutions, collaborate with stakeholders, and analyze data, focusing on achieving measurable business impact.

The Data Engineer II will design, develop, and maintain scalable, reliable data pipelines, collaborating with software engineering, analytics, and product teams.

The Senior Data Engineer will design, build, and optimize scalable data pipelines using PySpark, develop data models, and ensure data quality while collaborating with cross-functional teams.

Lead the development of adtech capabilities on a big data platform, collaborate with stakeholders, and improve internal processes while adhering to coding standards.

Design and build mission-critical, highly scalable data services and pipelines that analyze petabyte-scale blockchain data, architect low-latency data models, and collaborate with data scientists, backend engineers, and product managers to deliver production features.

The Senior Data Engineer designs and maintains data pipelines and systems, collaborates with teams, and optimizes data workflows using cloud technologies.

The Senior Data Engineer will manage end-to-end data processing, develop ETL/ELT pipelines, and collaborate with BI teams to provide insights using complex datasets.

The Senior Data Engineer will design and build data pipelines on Azure Databricks, ensuring data security and governance while collaborating with clients and vendors on projects.

The Staff Data Platform Engineer will build and optimize data pipelines, manage data processing workflows, and ensure scalability and reliability of backend platforms using Python, Spark, and Databricks.

Provide technical solutions and consulting for Apache Spark/Machine Learning issues, assisting customers in utilizing Databricks for analytics and AI tasks while performing troubleshooting and performance tuning.

The Senior Machine Learning Engineer at AB InBev will design and implement ML systems and pipelines to drive AI's mission for the Growth Group.

The Senior Data Engineer designs, develops, and maintains software solutions, leads projects, mentors juniors, and implements ETL/ELT pipelines using Azure tools.

The Staff Systems Engineer will lead the evolution of the SRE team for the Data Platform focusing on automation, reliability, incident management, and performance optimization while mentoring junior engineers.

The Staff/Lead Fullstack Engineer will enhance the Mimica Webapp by architecting scalable UI components, managing large datasets, and optimizing performance while collaborating with cross-functional teams.

The Senior Data Engineer will modernize the client's data platform, focusing on pipeline migration and implementing a dbt-based transformation framework, while collaborating with engineering teams for knowledge transfer.

The Data Integration Engineer is responsible for designing, maintaining, and optimizing data integration processes across various IT systems, ensuring data quality and alignment with business needs.

The Data Scientist will lead data-driven decision-making, develop machine learning models, design automated pipelines, and improve product performance.

Design, build, and maintain scalable Airflow-based data pipelines and reusable components. Implement CI/CD for deployments, enforce data governance and quality, monitor and troubleshoot workflows, document solutions, and mentor teammates on Airflow best practices.

The Data Engineer will analyze business data and create technical solutions, using SQL and other core tools to deliver data products.