Worked on Ingesting the source data in raw format from different types of files (CSV, Parquet), transform it and then persist into target data warehouse(Hive)We will be creating data loaders for each entity as background jobs using Pyspark scripts and running them on Autosys (Orchestration) for incremental dataResponsible for understanding requirements automation solutions using Pyspark and Hive to ingest and validate the data load.Created comprehensive documentation including design documents, user manuals, and technical specifications to facilitate smooth project transitions and support.Implemented monitoring solutions and established maintenance processes to ensure ongoing performance and stability of deployed applications.The project is to Consuming the source data in raw format, transform it and then persist into target data storesWe will be creating data loaders for each entity as background jobs using SQL Stored Procedure and running them as Kubernetes deployment for incremental data and historical backfillsCreating stored procedures to handle the different stages of dataIngestion of data to different tables in SQL server using Stored ProcedureOptimizing the SQL Stored Procedure based on the running time of SPResolving the tickets depends on the priorityMonitoring the scripts and resultant tables on a Daily, Weekly and Monthly basis and resolving if any failure or error occurredExploring various Stored Procedures and modifying it based on client's requirements

Handled customer inquiries, complaints, and returns professionally, ensuring a positive experience for all clients.Increased sales by building strong customer relationships and providing excellent service.Enhanced customer satisfaction with personalized product recommendations based on their needs and preferences.Opened, shelved and merchandised new products in visually appealing and organized displays for optimal sales promotions.