Top Data Engineer Jobs in Rio de Janeiro

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.

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.

The Software Engineer will design and implement search architecture to enhance data discoverability, handle significant feature ownership, perform code reviews, and mentor junior members in a Kubernetes environment.

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.

As a SQL & Snowflake Engineer, you'll develop SQL queries, analyze data schemas, and optimize performance within Snowflake, supporting feature development.

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.

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

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

Develop AI-powered data mapping recommendation platform, automate data extraction and validation, build scalable data pipelines, and manage data governance.

The Senior Software Engineer II will design, implement, scale, and maintain production systems, focusing on backend development, while collaborating with the Measurement team and mentoring others.

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.

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 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.

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

The Senior Data Engineer will lead the development of scalable data pipelines and infrastructure to support analytics, ensuring data quality and collaboration across teams.

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

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.