Ajay Kumar P Email & Phone Number

New Brunswick, New Jersey, United States

• Orchestrated the creation of dynamic data processing workflows using Azure Databricks and the distributed processing capabilities of Spark, to evaluate and comprehend client behavior in real-time.
• Collaborated on ETL tasks with a focus on maintaining data integrity and verifying the stability of real-time customer behavior analysis pipelines.
• Worked on migration of data from On - prem SQL server to Cloud databases (Azure Synapse Analytics (DW) & Azure SQL DB).
• Worked on Snowflake Schema, Data Modeling, Source to Target Mappings, Interface Matrix, and Design elements, while also designing and modifying Snowflake tables, views, and schemas to optimize retrieval and storage.
• Performed data quality issue analysis using Snow SQL by building analytical warehouses on Snowflake.
• Incorporating approaches such as Slowly Changing Dimension (SCD) and Change Data Capture (CDC) into microservices to preserve data integrity and effectively capture small changes, these pipelines smoothly interface.

Memphis, TN

• Implemented strategic data processing workflows in Azure Databricks, harnessing Spark's capabilities to execute large-scale data transformations, contributing significantly to operational efficiency in managing package.
• SCD and CDC techniques were integrated into these workflows to manage historical and incremental changes in customer data effectively.
• Implemented scalable and optimized Snowflake and Azure Synapse schemas, tables, and views, catering to complex reporting requirements and analytics queries, ultimately improving decision-making processes across the.
• Designed data ingestion pipelines utilizing Azure Event Hubs and Azure Functions, facilitating real-time data streaming into Azure Synapse for timely insights into package tracking and shipment information.
• Used Azure Data Lake Storage for efficient storage of raw and processed data, applying data partitioning and retention strategies to enhance data management and support the company's daily operations.
• Leveraged Azure Blob Storage for streamlined storage and retrieval of data files, implementing compression and encryption techniques to optimize costs and enhance data security.

Sunnyvale, CA

• Developed custom transformations and UDFs (User Defined Functions) in Scala and PySpark within Azure Databricks notebooks to address specific business logic requirements, enhancing data processing capabilities.
• Leveraged big data ecosystems, including Azure HDInsight which includes Hadoop, Spark, and other big data technologies for loading, and transforming diverse sets of structured, semi-structured, and unstructured data.
• Integrated Azure Cosmos DB with Hive within the Analytics Zone, optimizing data storage and retrieval processes.
• Applied Hive queries and Spark SQL on Azure HDInsight to meet specific business requirements, employing MapReduce-like functionalities for data analysis and processing.
• Implemented Azure DevOps Pipelines for automation in deployments, leading to expedited and more streamlined build and release processes.
• Designed and implemented data partitioning strategies in Azure Cosmos DB to optimize query performance and reduce latency in data retrieval operations.