• Designed and implemented efficient data pipelines using Python, SQL, and various ETL tools.• Managed and optimized databases including MySQL, PostgreSQL, and MongoDB for high availability and performance.• Developed and maintained CI/CD pipelines using Jenkins and Terraform, ensuring smooth and reliable deployments.• Collaborated with data scientists to build and deploy machine learning models in production.• Created data visualizations and dashboards using Tableau to provide actionable insights for stakeholders.• Leveraged AWS services (S3, EC2) for scalable data storage and processing solutions.• Utilized Docker for containerization to improve development and deployment workflows.• Utilized Python libraries such as Pandas, NumPy, SciPy, and Scikit-learn for scientific computing and data analysis.• Spearheaded the capacity-building initiative for a bank venturing into Big Data, leveraging open-source MongoDB and cloud technologies.• Implemented Git for version control, facilitating code management and collaboration across software versions.

• Conducted data analysis using Pandas and NumPy to support business decision-making.• Developed and implemented Data Access Control rules on cubes using APIs to ensure data security and confidentiality, reducing manual intervention by Python automation.• Supported technical teams and business units by creating dimensions and measures using DAX queries in PowerBI, resulting in interactive dashboards, reports, and analysis templates.• Developed Power BI dashboards for sell-thru analysis, leading to an 15% year-over-year revenue growth in the retail sales channel.• Utilized advanced Excel functions for dynamic stock analysis and procurement coordination.• Utilized Azure Databricks to perform data analytics, employing languages such as SQL and Python to derive insights and facilitate data-driven decision-making.• Performed Code release from one environment to another environment using release management in Azure DevOps.• Implemented REST APIs and integrated third-party data sources for comprehensive data collection.• Supported the migration of on-premises data infrastructure to AWS cloud, ensuring minimal downtime and data integrity.