Top Data Engineer Jobs in Rio de Janeiro

As an ETL Data Engineer, you will design and maintain ETL processes using Python and Azure Synapse Analytics, ensuring data accuracy and supporting collaboration across teams for data-driven insights.

The Data Engineer will implement ETL/ELT solutions, design data pipelines, ensure data security, and optimize data processing systems. Responsibilities include data transformation and compliance collaboration.

The role involves understanding customer processes, validating technical designs of applications, estimating project efforts, supporting implementation activities, and mentoring colleagues in application architecture.

Build and maintain BigQuery data pipelines, map warehouse schemas, and craft SQL to feed LLMs. Develop Claude Skills and Gemini Gems, collaborate on prompts, validate AI outputs, and design AI agents to automate eCommerce analytics and operational workflows.

Design, build, and deploy scalable data lakehouse and warehouse platforms; implement and optimize ETL/ELT pipelines (Databricks, dbt); develop data models and Medallion architecture layers; manage CI/CD and Infrastructure as Code (Azure DevOps, Terraform, CloudFormation); use cloud-native serverless offerings across major clouds; ensure data security and governance; integrate pipelines with BI tools like Tableau, Looker, and Power BI; communicate technical designs to stakeholders.

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.

Build and maintain complex datasets and ETL pipelines for analytics and BI. Design data warehouse solutions, write automation and scripts, profile and audit data, resolve data issues, and collaborate with data scientists and architects to improve data accessibility for business decision-making.

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

As a Data Engineer, you will design and maintain data products that support game performance tracking, create integrations with APIs, and enhance data platform reliability and performance.

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.

As an ETL Data Engineer, you will develop and maintain ETL processes using Python and Azure Synapse Analytics and collaborate with data scientists and analysts.

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.

As an AI Data Engineer, you will build end-to-end data pipelines, collaborate on AI features, and ensure data quality across our systems.

Design, build, and maintain cloud-native data pipelines ingesting industrial and historian data into GCP. Process large Parquet datasets, optimize BigQuery/Bigtable storage, support ML teams with production-ready datasets, integrate OT systems, troubleshoot data quality/performance, and operationalize analytics back into control environments.

The Data Engineer role involves developing and maintaining data pipelines, ensuring data quality, and collaborating with teams to deliver solutions tailored for financial services.

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

The Senior Data Engineer will manage SQL databases, focusing on optimization, performance tuning, and security while ensuring alignment with business objectives and mentoring team members.

Join a remote team to upgrade a Marketplace Analytics Data Platform. Responsibilities include developing data pipelines, managing data models, and ensuring data reliability for analytics purposes.

Responsible for managing data acquisition, curation, and publishing for analytics, developing data products, and creating scalable data pipelines.

Responsible for data collection to support model training operations. Involves working with cloud infrastructure, collaborating with AI scientists, and improving data processing.

The Data Engineer will migrate ETL jobs from Talend to Snowflake, validating and documenting the process, while building data quality frameworks and diagnostic tools.

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.

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.

Design and build production AI backend services, APIs, and data pipelines integrating LLMs and multimodal models; implement retrieval, context assembly, and grounded outputs; create evaluation and regression-testing frameworks; develop internal review tools and React operational UIs; ensure observability, monitoring, and scalable, cost-effective deployments. Own features end-to-end and collaborate with product and engineering stakeholders.

Design and develop the data management layer, focusing on scalability and integration for extensive data processing, while collaborating with various teams.