We are seeking a highly skilled
Azure Data Engineer with deep expertise in
Microsoft Fabric to design, implement, and optimize our next-generation data analytics platform. In this role, you will lead the transition and development of end-to-end data pipelines within a unified SaaS analytics environment. You will leverage the full power of OneLake, Lakehouses, and PySpark notebooks to build scalable, high-performance architectures that transform raw data into actionable enterprise insights.
Responsibilities
Responsibilities:- Fabric Architecture Design: Architect and deploy end-to-end data engineering solutions leveraging the Microsoft Fabric ecosystem including OneLake, Lakehouses, Warehouses, and Streamhouses.
- Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines using Fabric Datafactory, Pipelines, and Dataflows Gen2.
- Data Processing & Transformation: Write complex, optimized data transformation scripts using PySpark, Spark SQL, and Python within Fabric Notebooks.
- Modern Data Warehousing: Implement a Medallion Architecture (Bronze/Silver/Gold layers) inside OneLake utilizing Delta Lake formats for Delta Live Tables.
- Performance Tuning: Optimize query speeds and pipeline performance through strategic file partitioning, indexing, and workspace capacity management.
- Data Modeling & Analytics Integration: Construct and optimize Fabric Semantic Models to ensure seamless, high-performance integration with Power BI reporting.
- Governance & Security: Enforce enterprise data security using Fabric RBAC, Azure Key Vault, Managed Identities, and Microsoft Purview for metadata lineage.
- DevOps Integration: Implement CI/CD workflows using Git integration and Azure DevOps to automate code deployment across development, testing, and production environments.
Requirements
Required Skills & Qualifications- Education: Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related technical field.
- Core Experience: Minimum 3+ years of professional experience in Azure Data Engineering, with at least 1 year of dedicated hands-on experience working directly inside Microsoft Fabric.
- Tech Stack Mastery:
- Languages: Advanced proficiency in SQL, Python, and PySpark.
- Fabric Components: Deep knowledge of Fabric Lakehouse, Dataflows Gen2, Shortcuts, and Fabric Notebooks.
- Legacy Azure Services: Solid background in traditional Azure data stack tools like Azure Data Factory (ADF), Azure Synapse Analytics, and ADLS Gen2.
- Methodologies: Strong comprehension of Kimball data warehousing methodologies, dimensional modeling, and Delta Lake frameworks.
