Neelima Solinki

Developed and maintained scalable data pipelines using Azure Data Factory and Databricks to support high-volume data processing and business requirements. • Designed and implemented metadata-driven ETL/ELT pipelines with CDC-based incremental loading to improve performance and scalability. • Built a reusable automated transformation framework using a single Synapse notebook to process multiple tables across layers, reducing development effort by 60%. • Implemented Medallion Architecture (Bronze, Silver, Gold, ODS) for structured data processing and analytics. • Performed data transformations using PySpark (SCD Type 1 & 2) to support business and reporting requirements. • Monitored pipeline performance metrics, identified bottlenecks, and performed troubleshooting to improve system reliability and efficiency. • Collaborated with cross-functional teams including data analysts and business stakeholders to deploy pipelines into production environments. • Used Git-based version control and Azure DevOps CI/CD pipelines for efficient code management and deployment. • Maintained technical documentation for data pipelines, ensuring adherence to best practices and data governance standards. • Implemented basic data masking and security practices using Azure services. • Integrated Azure Logic Apps for alerting and Azure Key Vault for secure credential management. • Performed data analysis and built basic data visualizations to support business decisions and improve operational efficiency

• Developed and maintained scalable data pipelines using AzureData Factory and Databricks to support high-volume dataprocessing and business requirements. • Designed and implemented metadata-driven ETL/ELT pipelineswith CDC-based incremental loading to improve performanceand scalability. • Built a reusable automated transformation framework using asingle Synapse notebook to process multiple tables across layers,reducing development effort by 60%. • Implemented Medallion Architecture (Bronze, Silver, Gold, ODS)for structured data processing and analytics. • Performed data transformations using PySpark (SCD Type 1 & 2)to support business and reporting requirements. • Monitored pipeline performance metrics, identified bottlenecks,and performed troubleshooting to improve system reliability andefficiency. • Collaborated with cross-functional teams including data analystsand business stakeholders to deploy pipelines into productionenvironments. • Used Git-based version control and Azure DevOps CI/CDpipelines for efficient code management and deployment. • Maintained technical documentation for data pipelines, ensuringadherence to best practices and data governance standards. • Implemented basic data masking and security practices usingAzure services. • Integrated Azure Logic Apps for alerting and Azure Key Vault forsecure credential management. • Performed data analysis and built basic data visualizations tosupport business decisions and improve operational efficiency.

• Worked with Hadoop, Hive, Kafka, and PySpark for big dataprocessing. • Developed data processing workflows using Spark SQL. • Processed large datasets to derive insights and improvedecision-making.

GPA: 8.5