PANDIARAJAN PANDI

Azure-certified Data Engineer with 15+ years of experience in Data Warehousing, ETL/ELT pipeline design, and analytics. Expert in Fabric, Azure Synapse, Databricks, Azure Data Lake, Power BI, and modern data architecture. Proven ability to transform complex requirements into scalable, high-performance solutions that optimise operations, reduce costs, and drive actionable insights. Strong background in both on-premises and cloud migrations, with hands-on expertise in performance tuning and automation.

• Reduced ETL processing time by 40% through Databricks optimisation and efficient pipeline design.
• Delivered a self-service Power BI platform that improved reporting speed by 70% and reduced IT dependency.
• Led migration of a legacy data warehouse to Azure Synapse, cutting infrastructure costs by 30% while improving scalability.

Azure Data Engineering & Cloud Migration:

• Led multiple migrations from on-premises data warehouses to Azure Synapse, Databricks, and Microsoft Fabric, reducing infrastructure costs by up to 30% and improving scalability.

ETL/ELT & Pipeline Optimisation:

• Designed and optimised data pipelines using ADF, Databricks, Delta Lake, and Fabric Dataflows, reducing processing times by up to 40%.

Analytics & Reporting:

• Built self-service Power BI dashboards, interactive Fabric Power BI reports, and unified Lakehouse datasets that improved reporting speed by 70% and enabled real-time analytics.

Automation & DevOps:

• Developed automated CI/CD workflows for ADF, Databricks notebooks, Fabric Data Warehouse scripts, and SQL components using Azure DevOps, improving deployment efficiency and reliability.

Multi-Cloud & Hybrid Data Solutions:

• Designed and implemented data solutions on Azure (including Microsoft Fabric), AWS (S3, Glue, Lambda, Redshift), and hybrid environments.

Big Data Processing:

• Used PySpark, Spark SQL, and Hive for large-scale data transformations and analytics across financial, government, and enterprise domains.