Kannan Tamilraj

Support the migration of enterprise data platforms from Azure Synapse Analytics and on-premises data warehouses to Databricks. Develop and migrate ETL/ELT pipelines using PySpark, Spark SQL, and Databricks, translating existing SQL logic into Spark workflows. Implement Delta Lake processing with source-to-target validation, reconciliation, and data-quality checks to improve reliability of delivered data.

Designed and maintained scalable data architectures for automated ingestion, security, compliance, and governance. Built ETL pipelines using Azure Databricks, Azure Synapse Analytics, and Azure Data Factory to support downstream analytics. Implemented data validation and cleansing frameworks and monitored pipeline and SQL performance to support reliable production execution and continuous improvement.

Translated business requirements into data queries and ETL workflows, including data gathering, cleansing, and preparation for reporting and analysis. Developed scalable data pipelines using Azure Data Factory and Apache Spark and optimized SQL queries to improve transformation accuracy and reliability. Implemented event-driven and serverless workflows with Azure Functions and AWS Lambda, and added data-quality testing and monitoring for pipeline execution.

Developed Python integrations with Salesforce REST APIs to automate CRM case and task workflows. Built and maintained pipelines that ingest multi-source data into Snowflake using Python, SQL, and PySpark for centralized reporting. Created and tuned SQL queries and stored procedures, implemented Pytest unit tests, and used Airflow and AWS services to support reliable scheduled processing.