Top Data Engineer Jobs in Brazil

Design, build, and maintain scalable data and ML pipelines, manage vector stores and RAG workflows, integrate LLM frameworks for training and inference, enable semantic search and AI-driven BI, and document data processes while partnering with stakeholders.

Design, build, and operate Avra’s data platform services, ingestion pipelines, streaming integrations, and cloud-native deployments. Collaborate across AI, product, and infrastructure teams to ensure reliability, observability, and scalability of data products and APIs that power Foundation AI and customer-facing experiences.

Seeking a skilled Data Engineer with Apache Airflow experience to design, build, and maintain scalable data pipelines, optimize ETL processes, and provide technical leadership while collaborating with cross-functional teams.

Lead design and delivery of modular, automated, event-driven data pipelines and data models on Google Cloud. Build resilient, testable ETL/ELT processes, embed quality-by-design, coach junior engineers, collaborate with engineering and QA, and ensure data governance and privacy alignment while driving DevOps and IaC adoption across the Data function.

The Senior Data Engineer will modernize the client's data platform, focusing on pipeline migration and implementing a dbt-based transformation framework, while collaborating with engineering teams for knowledge transfer.

The Senior Data Engineer will design and build event-driven, near real-time data ingestion and Lakehouse architecture using tools like AWS, Snowflake, and Kafka, ensuring data reliability and governance.

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

The Senior AI/ML Engineer will architect and develop AI/ML solutions, collaborate with teams, and ensure deployment compliance, especially in healthcare.

The Analytics Engineer will build and maintain ETL data pipelines, manage data modeling, and collaborate with stakeholders to improve data processes.

Lead architecture and delivery of scalable data platforms and pipelines to support analytics, ML/AI products, reporting, integrations, and customer-facing data products. Productionize model outputs, enable LLM/VLM workflows, enforce data standards, ensure observability and data quality, and partner with Data Science to turn experiments into reliable production capabilities.

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.

Lead ownership of end-to-end data pipelines for Marketing, Product, and Growth analytics. Integrate multiple systems, model data, process GA4 event data at scale, build identity-resolution pipelines, and collaborate with product, marketing, and leadership to enable reliable data flows and actionable insights.

As a Senior Software Engineer, you will develop core data pipeline components for an AI-native data warehouse, oversee feature delivery, and ensure data quality and reliability.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

The role involves leading the database and data warehousing infrastructure, optimizing performance, collaborating with development, and integrating new technologies.

The Principal Engineer for Data Infrastructure will manage database systems and data warehousing, optimizing performance and integrating new technologies in a fast-paced fintech environment.

Design, build, and maintain large-scale, cloud-native data pipelines using Scala and Spark. Optimize distributed processing workloads, ensure reliability and performance at petabyte scale, contribute production-grade code, support deployments and monitoring, and collaborate within agile teams to deliver business-critical data platform solutions.

Support development and operation of scalable data pipelines and platform components. Apply software engineering best practices, assist with testing and releases, collaborate in agile teams, follow monitoring and incident protocols, and grow technical skills through mentorship and hands-on work.

The Software Engineer will manage data collection and the ingestion pipeline, improve cloud infrastructure, and collaborate with AI scientists on large-scale data projects.

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.

Lead architecture and implementation of a scalable, extensible data ingestion platform supporting batch, streaming, and event-driven pipelines. Ensure data quality, lineage, schema evolution, observability, security, and integration with control plane and DataOps. Mentor engineers, establish best practices, and deliver high-throughput, reliable ingestion across internal and third-party sources.

Design, build, and optimize SQL Server-based data layers and Azure data solutions. Own query performance, indexing, concurrency, CDC pipelines, ORM data access patterns (C#), and database CI/CD. Partner with engineers and architects, mentor team members, and ensure scalable, low-latency data platforms.

Own technical delivery and reliability of cloud-native data platform environments (AWS/Azure) for managed services clients. Build and maintain IaC and CI/CD pipelines, monitor and troubleshoot ETL/ELT jobs, provide technical leadership, mentor junior engineers, and contribute reusable templates, runbooks, and operational playbooks to standardize platform delivery.

Build and deploy Databricks Lakehouse pipelines on AWS to ingest, parse, and harmonize scientific instrument data for biopharma research. Prototype data acquisition, implement file parsers, design data models, develop Python ETL/ELT pipelines and tests, and work directly with customers to validate solutions.

As a Senior Data Engineer, you will build and maintain data pipelines, collaborate with teams to convert requirements into data solutions, and optimize cloud-based data infrastructure.