Data Engineer (Databricks & Azure) | Senior in Brazil, Indiana at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer (Databricks & Azure) | Senior based in Brazil.
This is a senior data engineering role focused on building and evolving modern Lakehouse architectures that power analytics and business intelligence at scale. You will play a key role in designing and maintaining the analytical consumption layer of a cloud data platform, ensuring data is reliable, well-governed, and optimized for performance. The position involves deep work with Databricks, Azure, and Power BI, connecting raw and curated data layers into actionable insights for business stakeholders. You will be responsible for ensuring data traceability, observability, and reprocessing capabilities across large-scale pipelines. Working in a highly technical and innovation-driven environment, you will collaborate with analytics and business teams to enable strategic decision-making. The role also requires strong ownership of data modeling, storage strategy, and governance practices within a modern Lakehouse ecosystem. This is an opportunity to shape enterprise-grade data platforms in a cloud-native and AI-oriented context.
- Design, structure, and maintain the analytical consumption and monitoring layer of the data platform.
- Build and manage Databricks SQL Warehouse environments for scalable and efficient data querying.
- Ensure proper separation between processing, storage, and analytical consumption layers in a Lakehouse architecture.
- Deliver governed datasets for Power BI and other enterprise analytics tools.
- Integrate Databricks with Azure Data Lake Storage (ADLS) and Power BI to enable end-to-end data flows.
- Manage historical storage and data persistence using Delta Lake, ensuring reliability and scalability.
- Implement data traceability, auditability, and reprocessing capabilities across pipelines.
- Define and maintain RAW, curated, and historical data strategies within the Lakehouse model.
- Establish and improve monitoring, governance, and data observability practices.
- Support business and analytics teams in building dashboards, KPIs, and strategic reporting solutions.
- Strong hands-on experience with Databricks SQL Warehouse in production environments.
- Solid knowledge of Lakehouse architecture and modern data platform design.
- Experience with Azure Data Lake Storage (ADLS).
- Proficiency in Delta Lake and Delta table management.
- Strong expertise in Power BI and analytical data modeling.
- Advanced SQL skills with experience in complex queries and optimization.
- Experience designing and maintaining ETL/ELT data pipelines.
- Knowledge of data governance, quality, lineage, and monitoring practices.
- Experience working in Azure cloud environments.
Differentials:
- Experience with Unity Catalog in Databricks.
- Knowledge of DataOps and/or MLOps practices.
- Experience with orchestration tools such as Azure Data Factory.
- Familiarity with data security models (RBAC/ABAC) and access control strategies.
- Competitive compensation package aligned with senior-level market standards.
- Remote or hybrid work flexibility depending on project allocation.
- Access to cutting-edge AI, data, and cloud-native technologies.
- Opportunity to work on large-scale, global data platforms.
- Continuous learning and development in Databricks, Azure, and modern data engineering practices.
- Exposure to AI-driven transformation initiatives and advanced analytics ecosystems.
- Collaborative and innovation-driven environment focused on technical excellence.