Senior Data Engineer (Microsoft Fabric) in Brazil, Indiana at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (Microsoft Fabric) based in Brazil.

This role is centered on building and owning a modern enterprise data platform using Microsoft Fabric, with direct impact on analytics, reporting, and data-driven decision-making. You will take technical ownership of end-to-end data engineering delivery, working closely with architects and stakeholders to design scalable, governed, and high-performance data solutions. The position combines hands-on engineering with architectural influence, covering everything from ingestion pipelines to semantic modeling and Power BI delivery.
You will operate in a highly autonomous environment where you are expected to make technical decisions, define best practices, and ensure engineering excellence.
A key part of the role involves building robust lakehouse architectures using modern medallion design principles and ensuring data quality and governance standards are met.
After the initial platform build, you will continue contributing to client-facing projects within a broader Data & AI practice.
This is a strong opportunity for someone who enjoys ownership, complexity, and shaping data platforms from the ground up.

• Design, build, and maintain enterprise-grade data solutions using Microsoft Fabric.
• Develop scalable data ingestion pipelines from APIs, databases, and file-based sources.
• Build and maintain Lakehouse architectures using the Medallion (Bronze, Silver, Gold) framework.
• Create robust data models and semantic layers to support analytics and business reporting.
• Develop and maintain Power BI semantic models, datasets, and dashboards.
• Implement data quality, validation, and reconciliation frameworks across pipelines.
• Design secure and governed data environments, including access controls and Row-Level Security (RLS).
• Build ETL/ELT processes using SQL, Python, and PySpark.
• Configure and manage Microsoft Fabric components such as OneLake, workspaces, and deployment pipelines.
• Collaborate with solution architects and stakeholders to deliver scalable and aligned data solutions.
• Produce and maintain technical documentation and engineering standards.
• Support future client projects within a Data & AI consulting practice.

• Strong commercial experience with Microsoft Fabric in production environments.
• Hands-on experience with Fabric Data Factory, Dataflows Gen2, Lakehouse, and OneLake.
• Advanced SQL skills and strong proficiency in Python and/or PySpark.
• Experience designing and implementing enterprise data models.
• Solid understanding of Medallion architecture and modern data lakehouse concepts.
• Proven experience building scalable ETL/ELT pipelines.
• Experience integrating REST APIs and external data sources.
• Knowledge of data quality, validation, and reconciliation practices.
• Strong Power BI experience, including semantic modeling and DAX.
• Understanding of Azure fundamentals (Entra ID, Key Vault, and related services).
• Ability to work independently on complex, end-to-end technical projects.
• Strong communication skills in English for collaboration with international stakeholders.
• Experience in consultancy environments or client-facing delivery (differential).
• Familiarity with CI/CD, Git workflows, Azure Synapse, or Data Factory (differential).
• Microsoft Fabric or Azure certifications (differential).

• Remote-first role (Brazil or Portugal based)
• Opportunity to work on cutting-edge Microsoft Fabric data platforms
• Exposure to international clients and global delivery teams
• Agile and collaborative work environment with strong ownership culture
• Ongoing training, mentoring, and professional development opportunities
• Ability to work across diverse data and AI projects
• Opportunity for technical leadership and architectural influence
• Travel opportunities depending on project needs
• Culture focused on learning, autonomy, and continuous improvement