1. Assisted management with the collection, organization, and analysis of quantitative and qualitative data using SQL. 2. Collected, cleaned, and organize financial and non-financial data in Python and developed a data pipeline. 3. Maintained and managed project repositories, resulting in an increase in team productivity using Azure DevOps.4. Developed a real-time data pipeline using Azure Event Hub, Azure stream analytics, Databricks, and Delta Tables that processed 10K+ data points in less than 5 minutes, resulting in a 40% increase in processing efficiency and created a live dashboard using PowerBI.

1. Extracted source data and organize it into a clean consumable format for business analysis. 2. Fetched looker data into python using APIs and did further data analysis and ML models. 3. Developed web analytical dashboards using Dash and Bokeh. 4. Used Apache spark, Azure Data Factory, Azure Databricks, Azure Data Lake, and/or Azure Functions and ETL pipeline.5. Worked on Twitter and Yelp APIs for customer sentimental analysis. 6. To create a structured dataset, have scrapped Docoh, Twitter, and Yelp platforms. 7. Created the model to predict the accuracy of the sentimental analysis.

1. Developed insurance domain web applications in Python Agile environments.2. Worked on REST APIs for web development and improved API performance average time by 15%.3. Written data pipelines in Python and SQL for transactional data from different sources using Azure Cloud.4. Worked on Data pipelines and PL/SQL query optimization for legacy systems and achieved 20% performance efficiency. 5. Design, build, and debug Data warehouse and Data Marts improving day-to-day operational performance.6. Used Jenkins, Kubernetes, and Jira for project monitoring and deployment and successfully worked on User Stories with business teams and leaders and translated business requirements and functional specifications.

1. Helped to gather requirements, solve schema discrepancies, to design the relational database schema, and Created data pipelines using PL/SQL (triggers, stored procedures).2. Pioneered a dynamic report generation framework using parameter configurations through SQL server database and utilized distributed and parallel computing capabilities to decrease the execution time to create multiple reports and performance improved by approximately 30%.3. Analyzed business requirements into technical requirements for data processing and visualizations.4. Designed and created on NoSQL database for unstructured file format and Hadoop ecosystem. (HDFS, HIVE)5. Created dashboards using Tableau (Data Visualization) to help the stakeholders analyze in a better way.