Data Warehouse Data Engineering
Role details
Job location
Tech stack
Job description
Design and deliver enterprise-scale data and analytics solutions using Microsoft Fabric, working closely with clients, business stakeholders, and engineering teams to build secure, scalable, and high-performance data platforms.
Key Roles & Responsibilities
Design end-to-end Microsoft Fabric architecture. Build solutions using OneLake, Lakehouse, Data Warehouse, Data Factory, Real-Time Intelligence, and Power BI. Implement Medallion Architecture (Bronze, Silver, Gold) and Delta Lake best practices. Develop scalable data ingestion, ETL/ELT, and orchestration pipelines using Fabric Data Factory and Spark. Design semantic models, Direct Lake, dashboards, and reports in Power BI. Define data governance, security, and lineage using Microsoft Purview and Microsoft Entra ID. Optimize Fabric capacity, Spark workloads, Warehouse performance, and Power BI reports. Implement CI/CD using Git integration and Fabric Deployment Pipelines. Lead client workshops, architecture reviews, solution design, and technical delivery. Mentor technical teams and ensure adherence to architecture and coding standards.
Core Microsoft Fabric Components
OneLake Data Factory Lakehouse Data Warehouse Data Engineering (Spark, PySpark) Real-Time Intelligence (Eventstream, Eventhouse, KQL) Power BI (Semantic Models, Direct Lake, DAX) Data Science & AI Microsoft Purview Fabric Deployment Pipelines & Git Integration
Requirements
Microsoft Fabric Azure Data Platform SQL, PySpark, Python Power BI & DAX Delta Lake & Medallion Architecture Data Modeling Microsoft Purview CI/CD & DevOps Stakeholder Management and Solution Architecture