Top Data Engineer Jobs in Sao Paulo

As a Data Engineer, you'll implement data extraction, build scalable data processing pipelines, manage data infrastructure, and enforce data governance and best practices.

Lead the entire data ecosystem including data warehousing, pipelines, and BI foundations, while providing technical mentorship and ensuring data quality.

The Data Engineer will develop enterprise applications, manage data requirements, communicate project risks, engage in the development lifecycle, and educate clients about machine learning best practices.

As a Senior Data Engineer, you'll build and optimize data pipelines for an AI platform, ensuring data integrity and performance while collaborating with various teams.

Develop and maintain data models, monitor data pipelines, improve data accessibility for business intelligence, and collaborate with teams on data integration projects.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

The Data Engineer will develop ETL processes, build data pipelines, and optimize data architecture while collaborating with stakeholders and ensuring data integrity.

As a Data Engineer, you'll maintain and enhance a data ingestion pipeline, collaborate with data scientists and engineers, and implement features for efficiency and scalability.

As a Midlevel Data Engineer, you will develop data models, design data pipelines, and ensure data quality, while collaborating with different teams to improve user experiences.

Develop and maintain data models, monitor data pipelines, collaborate with teams to enhance data accessibility, and ensure data quality in a cloud environment.

As a Software Engineer, you will design and build scalable data services to analyze blockchain transactions, collaborating with data scientists and engineers.

The Data Engineer will design, build, and maintain scalable data pipelines using Apache Airflow, ensuring reliable data delivery and optimizing ETL processes.

The Business Intelligence Data Analyst role involves data modeling, analyzing datasets for actionable recommendations, and driving automation solutions for business processes while ensuring effective governance and tracking KPIs.

Join an AI-driven research project as a Frontend Developer, designing and building user-friendly web applications using modern JavaScript frameworks and strong UI/UX principles.

As a Data Engineer, you will design and develop data processing pipelines, collaborate with data scientists, and ensure data quality. You'll utilize modern tools and frameworks to manage data applications, focusing on data governance and stakeholder management.

Design, develop, and maintain data pipelines and ETL processes; ensure data quality and optimize performance; collaborate with cross-functional teams and mentor others.

The Senior Software Engineer will lead the design and development of scalable data acquisition systems, mentor engineers, and ensure high-quality code practices while integrating various internal and external data sources.

As a Staff Technical Solutions Engineer, you will resolve customer issues related to Apache Spark, provide guidance on best practices, and assist customers in optimizing their use of Databricks products.

The Senior Lead Data Engineer will optimize data pipelines, develop applications, and ensure data quality for BI reporting in LatAm and EEMEA regions.

Develop and maintain ETL pipelines and data integrations, optimize data flows, and troubleshoot production issues using AWS, Python, and SQL.

Seeking a Senior Data Engineer to build and optimize data pipelines, maintain data warehouses, and enable advanced analytics across the organization with a focus on quality and governance.

As a Senior Data Engineer, you'll build and maintain data pipelines, ensuring efficient data flow and collaborating with teams to deliver reliable solutions for the company.

The Data Engineer will analyze business data stories and translate them into technical designs, focusing on building and implementing data products with minimal guidance.

Design and maintain data ingestion frameworks using AWS technologies, ensuring integration with Snowflake, and collaborating across teams for project delivery.

Design, build, and maintain data pipelines, optimize existing ETL processes, and collaborate with teams to deliver structured datasets and support analytics initiatives.