Key Responsibilities

End-to-End Data Pipeline Development

• Design, develop, and manage scalable data pipelines using Microsoft Fabric (Data Pipelines, Lakehouse, Warehouse, OneLake) and Azure Data Factory
• Build robust ETL/ELT workflows supporting batch and near real-time data processing
• Ensure efficient data ingestion from multiple sources including APIs, RDBMS, files, and streaming systems

Lakehouse Architecture & Data Modeling

• Implement Medallion Architecture (Bronze, Silver, Gold layers) for enterprise data platforms
• Design and optimize data models using star and snowflake schemas
• Support modern lakehouse and data warehousing architectures

Data Processing & Engineering

• Develop data transformation logic using PySpark, Python, Spark SQL, and SQL
• Optimize T-SQL queries, stored procedures, and database performance
• Implement incremental loading, CDC, and watermarking techniques

Cloud Integration & Storage Management

• Work with Azure Data Lake Storage Gen2, Azure Blob Storage, and OneLake
• Manage structured and unstructured data across distributed storage systems
• Integrate datasets with Power BI for analytics and reporting

Monitoring, Governance & Optimization

• Implement data quality checks, monitoring, logging, and error handling frameworks
• Use Azure and Fabric monitoring tools for performance optimization
• Ensure compliance with data governance, lineage, and security standards (Microsoft Purview preferred)

Migration & Modernization

• Support migration from Azure Data Factory and Databricks to Microsoft Fabric
• Contribute to modernization of enterprise data platforms
• Ensure smooth transition with minimal disruption to data pipelines

Collaboration & Leadership

• Work closely with architects, analysts, and business stakeholders
• Translate business requirements into scalable technical solutions
• Provide technical guidance and mentorship to junior engineers