Top Data Engineer Jobs in Rio de Janeiro

As an ETL Data Engineer, you will design and maintain data integration processes using Python and Azure Synapse Analytics, ensuring data accuracy for insights. Collaborate with stakeholders on data warehousing, quality, monitoring, and performance optimization while adhering to data governance standards.

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.

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.

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.

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.

As an ETL Data Engineer, you will develop and maintain ETL processes, optimize data storage, ensure data quality, and collaborate with stakeholders.

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.

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

Design and maintain Azure-based data pipelines, model and integrate on-prem and cloud data, build Power BI/Tableau dashboards, write complex SQL/Kusto queries, manage cloud costs, and guide teams on data best practices within Agile teams.

Lead FinOps and data initiatives to optimize Databricks workloads, monitor cloud spend, build executive dashboards, define FinOps governance, and partner cross-functionally to drive cost-efficient architecture and measurable business outcomes.

Build, maintain, and monitor data pipelines and transformations using SQL, Python, and Spark. Troubleshoot pipeline failures and data quality issues, implement schema mappings and validation rules, support metadata, lineage, and data classification, automate operational tasks, contribute to testing and monitoring, and follow security, governance, and engineering best practices while collaborating with cross-functional teams.

Design and operate scalable, low-latency ETL/ELT and streaming data pipelines across ClickHouse, Postgres, Athena, and cloud sources; manage schema evolution, data modeling, sharding/partitioning, CI/CD for data, monitoring, and lineage; collaborate with engineers and data scientists to productionize ML/AI models and mentor team members.

Design, build, and maintain scalable cloud-native data pipelines and ELT/ETL workflows in AWS. Develop and optimize Snowflake data models, ingest structured and unstructured data, and use Databricks/Spark to process large datasets. Implement data quality, governance, monitoring, and orchestration. Collaborate with data scientists, analysts, and engineers to support analytics, reporting, and AI/ML initiatives while optimizing performance and cost.

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

Design and build scalable Snowflake-based data models and pipelines using SQL and Python. Integrate data via APIs, optimize performance, and collaborate cross-functionally to support reporting and analytics while improving data engineering standards.

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.

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

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

As a Data Engineer, design and maintain data pipelines and infrastructure, collaborate with teams for efficient data delivery, and optimize data storage and retrieval processes.

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 scalable ELT/ETL pipelines and data models for cloud cost attribution and financial reporting. Design a Cloud Economics data warehouse, perform end-to-end validation and auditing, automate cost-optimization recommendations, and deliver high-quality datasets for Product, Engineering, and Finance stakeholders.