Top Data Engineer Jobs in Brasilia

As an ETL Data Engineer, you will develop and maintain data integration processes using Python and Azure Synapse Analytics, ensuring data accuracy and availability for analytics. You'll collaborate with data teams to optimize data management, implement quality checks, and document processes within a supportive consulting environment.

As an ETL Data Engineer, you will design, develop, and maintain ETL processes using Python and Azure Synapse Analytics, ensuring data accuracy and availability while collaborating with data scientists and analysts.

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

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.

Design, build, and maintain ETL pipelines and data transformations (Microsoft Fabric, SQL, Python, Power Query). Implement data quality checks, incremental loads, dimensional models, and documentation. Troubleshoot operational issues, support UAT, and collaborate with leads on architecture and semantic models to power analytics and reporting for the Mortgage Cadence platform.

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

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.

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 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.

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.

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.

As a Senior Data Engineer at Zencore, you will leverage Google Cloud to assist clients in data transformation and application modernization, covering ETL/ELT, data warehousing, and streaming data systems.

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.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Design, develop, and maintain scalable data ingestion, transformation, and orchestration pipelines in Palantir Foundry using Python and PySpark. Create reporting-ready datasets and data models for Power BI, implement ETL/ELT processes, ensure data quality and monitoring, troubleshoot production issues, and document solutions while collaborating with cross-functional stakeholders.

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.