Azure and M365 Projects

Azure Migration and Modernization of ETL Processes and Infrastructure
  • Project: ETL Modernization and Infrastructure Migration to Azure
  • Role: Solution Architect / Data Engineering Lead
  • Team: 15 members including Data Engineers, ETL Developers, Azure Infrastructure Specialists, and cross-functional stakeholders
  • Objective:
    • Migrate legacy on-prem Windows Servers and SQL Server databases to Azure VM and Azure SQL PaaS.
    • Modernize SSIS ETL pipelines for document and metadata processing.
    • Enable scalable, automated, and highly available data workflows in Azure.
    • Reduce on-prem maintenance cost and operational risk.
  • Azure VMs (Windows Server 2016)
  • Azure SQL Database (PaaS)
  • SSIS / SSRS
  • SQL Server Management Studio
  • Power BI
  • Docker (for legacy ECM apps)
  • SharePoint Online
  • Designed Azure-based architecture, including VM sizing, SQL PaaS, and high availability planning.
  • Migrated on-prem SSIS ETL packages to Azure VM-hosted SQL Server, optimizing for performance and reliability.
  • Re-engineered SSIS packages to process document metadata from legacy ECM systems efficiently.
  • Built Azure SQL tables and schemas to capture document and operational data.
  • Implemented automation for metadata extraction, validation, and ingestion from multiple sources.
  • Configured Azure DR and HA strategies, including geo-redundant backups and site recovery.
  • Conducted POCs for performance tuning of SSIS workflows and SSRS reporting.
  • Collaborated with cross-functional teams and vendors to provision Azure infrastructure and ensure secure access.
  • Developed technical documentation, deployment guides, and trained internal teams on new cloud-based ETL workflows.
  • Monitored pipeline performance post-migration and ensured data quality and integrity.
  • Successfully migrated all on-prem SSIS ETL workflows to Azure VMs and Azure SQL.
  • Reduced infrastructure maintenance cost by ~40% by leveraging Azure PaaS and VM-based ETL hosting.
  • Improved ETL execution performance by ~50% through optimized SSIS workflows and SQL tuning.
  • Enabled high availability and disaster recovery for mission-critical financial data.