Data and Analytics Team

- Facilitated collaboration across multiple departments to gain a deep understanding of and prioritize client requirements, resulting in a 20% improvement in product adoption rates and a 10% reduction in churn rates. - Spearheaded various insurance and travel trip upgrade projects, collaborating closely with clients to enhance customer satisfaction scores by 20% and increase annual revenue by $500,000.- Utilized PySpark and Informatica BDM for data cleaning and transformation, ensuring high-quality, usable data for analytics and reporting.- Enhanced operational efficiency through implementing IBM Tivoli Workload Scheduler, achieving a 25% reduction in job processing errors, a 30% improvement in scheduling accuracy, and saving over 50 monthly hours. - Streamlined workflow processes with Git and Jenkins for efficient code management and deployment, ensuring smooth and error-free operations.

- Developed an application for insurance and travel trip upgrade data, leveraging a robust tech stack including Python, Hive, Informatica BDM, PySpark, Jenkins Pipeline, and IBM Tivoli Workload Scheduler (TWS).- Managed data flows from source Lakehouse or servers to our DataLakes using Python and Informatica BDM, ensuring seamless data integration and accessibility- Optimized data storage solutions using Hadoop and Amazon S3, improving data retrieval times and reducing storage costs- Delivered scalable data solutions, fostering team synergy to meet project deadlines and exceed performance expectations.- Utilized Jira to maintain transparency and accountability in dynamic project environments, tracking progress and ensuring timely delivery.