Top Data Engineer Jobs in Brazil

Lead data engineering strategy and architecture, design scalable batch and streaming data platforms, drive AI-centric data initiatives, implement CI/CD and IaC, improve data quality/observability/governance, mentor engineers, and deliver large cross-functional production initiatives.

Lead design and implementation of scalable data pipelines and cloud data warehousing solutions. Partner with stakeholders to translate requirements, build and optimize complex SQL, perform root-cause analysis, and deliver dashboards and reports for end-user analytics.

Build, deploy, and maintain production-grade ML models and data pipelines in cloud environments. Perform EDA and feature engineering, monitor model performance and drift, and collaborate with engineering and business stakeholders. Contribute to AI/LLM initiatives and ensure solutions operate reliably in production.

Design, build, and maintain scalable data pipelines and architectures; ensure data quality and reliability; enable self-service analytics; collaborate with Data Science, Data Ops, and product teams; troubleshoot and optimize data systems; document and improve data workflows and infrastructure.

Design, build and maintain scalable, observable end-to-end data pipelines on AWS. Ingest data from REST APIs, transform and load into data lakes/warehouses, implement orchestration and monitoring, and explain technical solutions to stakeholders.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Design, build, and scale GTM data pipelines, lakes, and analytics to support sales, marketing, and customer success. Ensure data integrity across GTM systems, implement batch and streaming ingestion, develop enrichment/LLM pipelines, create semantic models in dbt, and automate revenue workflows and ICP/territory scoring.

Design, build, and maintain scalable data pipelines, ETL processes, and data models; ensure data quality and consistency; work with cloud data platforms and BI tools to create dashboards and data products; collaborate with analysts, data scientists, and stakeholders to translate business needs into technical solutions.

Build and maintain scalable, high-performance data pipelines and platforms using Spark/Scala/Python. Own end-to-end projects, collaborate with product and global teams, mentor junior engineers, implement testing and performance tuning, and contribute to the technical roadmap.

Own and deliver end-to-end data engineering projects: design, build, test, deploy, and maintain scalable big-data pipelines and APIs. Collaborate with product and global teams, mentor junior engineers, monitor performance, and drive technical roadmap and stability improvements.

Design, build, and optimize semantic Tableau data models, dashboards, reports, and datasets. Integrate and validate Databricks data pipelines, maintain data ingestion from APIs and databases, lead Looker-to-Databricks+Tableau migration, ensure data governance, performance, and security, and collaborate with stakeholders to translate business needs into scalable BI solutions.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.