Top Data Engineer Jobs in Sao Paulo

Transform data into actionable insights using SQL and Python. Develop models, create dashboards, and present findings to senior leadership.

The Data Engineer will design and implement scalable data solutions, optimize data flow, build data platforms, and work with ETL/ELT processes.

As a Sr. Data Engineer, you'll build and scale high-throughput streaming pipelines, model real estate datasets, and improve data quality using AI-driven tools in a fast-paced environment.

Develop and maintain ETL processes in Azure Synapse Analytics, ensuring data accuracy and performance. Collaborate with teams to optimize data workflows and implement data quality checks.

The role involves providing technical expertise in database marketing solutions, including creating code, operational support, and participating in design reviews.

This role provides technical expertise for database marketing solutions, focuses on SQL proficiency, and involves creating and modifying database code.

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

As a Senior Data Engineer, you will create scalable backend services, manage data pipelines, and integrate AI features, ensuring performance and reliability.

Join the Data Foundry team as a Data Engineer, building pipelines and infrastructure for AI workflows, ensuring data quality and governance while maintaining and optimizing ETL processes.

The role involves designing and optimizing data pipelines, migrating legacy systems to Databricks, and collaborating with clients in a consulting capacity.

As a Data Engineer, you'll design and maintain data models and pipelines, collaborate with teams, and ensure high-quality data for analytics.

The Data Engineer will build and maintain data pipelines, improve workflows, support data modeling, and enhance system reliability while collaborating with senior engineers.

The Data Engineer will design and implement scalable data platforms, build data pipelines, collaborate with teams to ensure data quality, and streamline processes using AWS services and big data technologies.

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.

The Data Engineer role involves creating and managing data pipelines, optimizing data infrastructure, and automating data processes using tools like Snowflake, dbt, and Terraform.

The Data Engineer will design and maintain scalable data pipelines and support ML workflows, ensuring reliability and performance of data systems.

Define and implement architectural solutions for data pipelines, drive best practices for ETL workflows, and lead client engagement in a consulting environment.

As a Software Engineer for Data Infrastructure at Speechify, you will manage data collection, enhance cloud infrastructure, and collaborate with researchers to optimize datasets for AI models.

We are looking for a Staff Software Engineer for our MLS data platform to develop data pipelines, backend services, and AI-driven features for the real estate industry.

As a Senior Data Engineer, you will design, develop, and maintain data pipelines and models, leading analytics initiatives and fostering collaboration with stakeholders to address complex business challenges using data solutions.

Seeking a Data Engineer with 5+ years experience in ETL/ELT design, data analysis, and cloud-based solutions. Responsibilities include building data pipelines, maintaining data warehouses, and collaborating with stakeholders on data initiatives.

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

Lead the design and implementation of robust data pipelines and ecosystems. Ensure scalability and reliability while mentoring team members in best practices.

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.