Mid Level Data Engineer, Brazil
Confirmed on the employer's own hiring board on Nov 5, 2026. First seen by Alion on Oct 30, 2026. CI&T scores A on the Alion truth index.
We are currently offering an opportunity for a Mid-Level Data Analyst to join our team. The role focuses on supporting, maintaining, and improving our data and business intelligence solutions, ensuring reliable data integration, efficient processing, and high-quality reporting.
We are looking for a professional with intermediate-level experience in data analysis, business intelligence, and data integration, with strong analytical and problem-solving skills. The ideal candidate should be comfortable working with SQL Server, Power BI, SSIS, data warehouses, and enterprise data integration processes, while collaborating with technical and business teams to support data-driven decision-making.
Required Skills and Responsibilities
Power BI Management: Develop, maintain, and optimize Power BI reports, dashboards, semantic models, and data refresh processes.
SSIS Package Management: Develop, maintain, troubleshoot, and optimize SQL Server Integration Services (SSIS) packages and ETL workflows.
Data Pipeline Management: Monitor, maintain, and optimize data pipelines to ensure reliable, efficient, and timely data processing.
Data Warehouse Management: Maintain and enhance data warehouse solutions, ensuring data integrity, consistency, performance, and availability.
Data Integration: Manage and support integrations between enterprise systems, databases, and external data sources.
OData Services: Maintain, monitor, and troubleshoot OData endpoints, ensuring efficient data extraction, pagination, and integration with downstream systems.
Troubleshooting and Performance Optimization: Identify root causes of technical issues, investigate pipeline failures, optimize SQL queries and data processing workflows, and implement corrective actions.
Monitoring and Operational Support: Monitor scheduled jobs, data refreshes, integrations, and pipeline execution to ensure operational stability and adherence to service-level expectations.
Data Quality and Integrity: Implement validation mechanisms and resolve data inconsistencies across source systems, integration layers, and data warehouse environments.
Continuous Improvement: Identify opportunities to improve system reliability, processing performance, maintainability, and operational efficiency.
- English: Advanced english is required.