● Spearheaded the development of innovative clinical dashboards for clients, utilizing Tableau to deliver actionable insights. Maintained and resolved client’s tickets using JIRA.● Implemented and managed relational databases like Microsoft SQL Server, Oracle and NoSQL databases like MongoDB and Apache HBase. Reduced query execution time by 30% through query optimization techniques, enhancing data processing efficiency.● Utilized SQL Server Reporting Services (SSRS) and SQL Server Integration Services (SSIS) to develop and automate robust reporting and data integration solutions.● Led the design and development of company’s framework by fixing defects and introducing new enhancements in the framework by using SQL, Python, Core Java, JavaScript, ES6, Typescript and Angular JS. Leveraged shell Scripting, PowerShell, and Unix/Linux environments to automate routine tasks and streamline data processing workflows, enhancing overall operational efficiency.● Developed Core Java service that can handle user requests efficiently and provide appropriate results based on the requests received using Maven, Java, and REST API. Deployed artefacts with CI/CD pipelines using Jenkins.● Demonstrated proficiency in AWS services including EC2, EMR, and Redshift, leveraging cloud Data Lake platforms for scalable and cost-effective data storage and analysis.

● Collaborated closely with cross-functional teams and stakeholders at Bell to develop data-driven solutions addressing critical business challenges. Utilized Data Visualization tools like Tableau to create dashboards for Bell Media, resulting in a 25% improvement in operational efficiency.● Utilized Big Data Technologies such as Hadoop, Spark, and Hive at Bell, enhancing data processing capabilities and optimizing performance metrics.● Extensively used SQL for implementation on business uses cases. Optimized complex SQL queries for better performance, reducing the execution time by almost 50% on Hadoop Cluster. ● Applied statistical modelling techniques, including linear regression, to predict service availability for Bell Media, achieving a 99% accuracy rate. Implemented Machine Learning models, such as Regression and Clustering, using Python libraries like Pandas, NumPy, Scikit-Learn and TensorFlow to optimize performance metrics and predict customer call rates.● Successfully migrated Bell workflows to Google Cloud Platform, reducing system execution time to seconds and improving overall operational efficiency. Experience includes working with AWS and Azure, creating EC2 instances, S3 buckets, and extracting data from S3 to tables in AWS Redshift, Amazon Glue, Quicksight, and SageMaker

● Led the design and development of company’s framework by fixing defects and introducing new enhancements in the framework by using SQL, Python, Core Java, JavaScript, ES6.● Actively communicated with stakeholders and developed dashboards on patient data with multiple components like Allergies, Medications, Vitals, Visits etc using Power BI● Worked with Anomaly detection on patient groups at risk, Descriptive and Predictive Analysis on multiple patient data use cases.● Worked on CI/CD pipelines to deploy artefacts on Jenkins.● Experience working on GitLab/GitHub for pushing code & raising Pull Requests● Worked under Scrum/Agile Methodology