Description

You will architect and implement enterprise-grade Microsoft Fabric Lakehouse solutions to support scalable analytics workloads.

This role is on-site.

Responsibilities

• Architect and implement Lakehouse solutions using OneLake, Fabric Data Engineering, Warehouses, and Pipelines.
• Design and develop ETL/ELT pipelines using Fabric Data Factory, Azure Data Factory (ADF), and Synapse for batch and incremental processing.
• Build distributed data processing frameworks using PySpark, Spark SQL, and Fabric notebooks for structured, semi-structured, and streaming data.
• Develop modern Lakehouse architectures with Medallion (Bronze/Silver/Gold) layers and optimized data modeling strategies.
• Lead legacy platform modernization, migrating on-prem SQL Server, SSIS, or Hadoop ecosystems to Microsoft Fabric.

Required Skills

• 10+ years of experience in data engineering roles.
• Strong hands-on expertise in Microsoft Fabric components: Lakehouse, OneLake, Data Pipelines, and Warehouse.
• Deep knowledge of Azure Data Factory (ADF) and Azure Synapse Analytics.
• Proficiency in SQL, T-SQL, and Spark SQL for data transformation and query optimization.
• Programming expertise in Python and PySpark for distributed processing.
• Experience integrating and optimizing Power BI datasets, semantic models, and Direct Lake connectivity.
• Strong understanding of data modeling patterns, including Star Schema and Snowflake Schema.
• Hands-on experience with enterprise data ingestion from ADLS, APIs, SQL databases, and ERP/CRM systems.
• Experience implementing DevOps and CI/CD pipelines using Azure DevOps and Git integration.

Key Skills

Education

Not specified