Developed a scalable pharmacy management system to optimize medication dispensing and inventory management. Automated daily tasks, ensuring accurate prescriptions, optimal stock levels, and regulatory compliance.● The MNK Pharmacy project focused on creating a scalable and efficient pharmacy management system to optimize the medication dispensing process and inventory management.● Automated key pharmacy operations, including prescription handling and inventory control, ensuring 99.5% accuracy in medication dispensing and maintaining optimal stock levels, reducing stock discrepancies by 15%.● Converted QlikView code into Databricks equivalents, translating complex QlikView scripting and data transformation logic into PySpark and SQL, leading to 30% faster processing times and enhancing the system's scalability.

At Infosys, I had an enriching experience in a highly positive work environment, where I had the opportunity to apply and enhance my skills in developing robust solutions for business requirements. Starting from the ground up, I gained valuable insights into the company's operations and dedicated myself to self-improvement. Throughout my tenure, I successfully navigated diverse technological stacks in my projects. Through effective collaboration and leveraging my leadership abilities, I consistently delivered projects and knowledge transfers ahead of schedule.● Analyzed 100+ user stories and acceptance criteria to clarify project scope and desired outcomes, resolving ambiguities and reducing project delays by 15%.● Provided task estimations based on detailed project analysis, contributing to a more accurate project timeline with an improved estimation accuracy of 90%, ensuring resources were allocated effectively.● Utilized PySpark to perform data cleaning, transformation, and integration on 10+ TB of data, ensuring data accuracy and consistency, which improved overall processing efficiency by 20% and supported enhanced analytics for business insights.

The client ABC Bank has decided to migrate its existing data warehouse from Snowflake source systems to cloud to modernize with focus on establishing next-generation analytical services and leveraging cloud capabilities, scale, speed, and performance.● Developed a scalable Native Azure solution for Salesforce to Azure Synapse ingestion, streamlining data flow across multiple departments and improving data pipeline efficiency by 30%.● It helped to move ingestion pipelines from Snowflake and saved cost for heavy license fee● This generic framework helped other business units for smooth ingestion of newly onboarded Snowflake object into Azure Synapse.

The project focused on designing and deploying a scalable, fault-tolerant data storage and processing solution using HDFS. It handled large volumes of structured and unstructured data across multiple nodes, ensuring reliable storage and enhanced processing capabilities. ● Designed and configured HDFS clusters with Namenode and Datanode setup for distributed storage. Loading the transformed data into the desired destination, such as a database.● Built solution using Hadoop Ecosystem (HDFS, YARN), Spark and Python● Managed data ingestion pipelines using Apache Sqoop for importing data from relational databases and Apache Flume for real-time log collection.