Naga Deepthi Kanamarlapudi

Demonstrated expertise in crafting robust ETL pipelines using Spark Data Frames, Azure Databricks, and Palantir Foundry to extract, transform, and load diverse vehicle information data. I successfully optimized ETL processes for large-scale insurance datasets, leveraging techniques such as partitioning, caching, and broadcast variables. I collaborated closely with stakeholders to ensure data quality and alignment with analytical needs. I demonstrated proficiency in building data pipelines using Azure Data Factory and integrating with Power BI for reporting. I am also experienced in implementing data quality frameworks and metrics to maintain data integrity.

Demonstrated proficiency in the entire software development lifecycle, from requirements gathering to testing, within an agile environment. I actively contributed to ETL pipeline development using PySpark transformations and actions in Azure Databricks and Palantir Foundry. I am skilled in designing and developing Spark/PySpark applications for data parsing, validation, and transformation. I am also proficient in data quality assurance, including data cleansing, deduplication, and outlier removal. I am experienced in building data pipelines using Azure Data Factory and creating visualizations for effective analysis. I collaborated effectively with both onshore and offshore teams to ensure successful project delivery.