- Designed and implemented scalable data pipelines on Google Cloud Platform (GCP) using BigQuery, Cloud Dataflow, and Cloud Pub/Sub to streamline data processing and analysis.- Developed and optimized ETL processes to efficiently ingest, process, and store large volumes of data, reducing processing time by 40% using Google Cloud Storage and BigQuery.- Built ETL solutions using AWS services like S3, Redshift, DMS, and Lambda for seamless data ingestion and transformation.- Automated… Show more - Designed and implemented scalable data pipelines on Google Cloud Platform (GCP) using BigQuery, Cloud Dataflow, and Cloud Pub/Sub to streamline data processing and analysis.- Developed and optimized ETL processes to efficiently ingest, process, and store large volumes of data, reducing processing time by 40% using Google Cloud Storage and BigQuery.- Built ETL solutions using AWS services like S3, Redshift, DMS, and Lambda for seamless data ingestion and transformation.- Automated data pipelines with Airflow and Spark SQL, and integrated real-time monitoring with Lambda and CloudWatch to support dynamic workflows.- Created fraud detection dashboards in Tableau, conducted big data analytics in Apache Spark, and improved data quality with SQL and Hive scripts. Show less

- Designed Fidelity’s risk management platform on Google Cloud Platform (GCP), integrating multiple data sources to provide real-time insights into asset performance, risk exposure, and compliance.- Established data ingestion pipelines using Cloud Dataflow, transforming data with Dataproc to produce standardized, high-quality datasets.- Architected a Google Cloud Storage structure to securely store financial data and optimized data processing in BigQuery, reducing processing times by… Show more - Designed Fidelity’s risk management platform on Google Cloud Platform (GCP), integrating multiple data sources to provide real-time insights into asset performance, risk exposure, and compliance.- Established data ingestion pipelines using Cloud Dataflow, transforming data with Dataproc to produce standardized, high-quality datasets.- Architected a Google Cloud Storage structure to securely store financial data and optimized data processing in BigQuery, reducing processing times by 25%.- Built Looker dashboards to visualize portfolio risk metrics and performance, enabling timely, data-driven decision-making.- Collaborated with compliance teams to ensure data handling met regulatory standards, and employed Vertex AI to support risk prediction model development.*Impact*: Reduced risk assessment times by 40% and enabled proactive portfolio management, significantly enhancing Fidelity’s data-driven decision-making. Show less

- Built a scalable, cloud-based platform to analyze and process insurance claims data in real-time, enabling predictive modeling, fraud detection, and customer retention strategies.- Developed a resilient multi-tier cloud infrastructure on AWS using EC2, RDS, DynamoDB, and S3, and automated deployments with CloudFormation.- Conducted exploratory data analysis and developed predictive models in Python, with real-time insights visualized in Tableau dashboards.- Designed serverless ETL… Show more - Built a scalable, cloud-based platform to analyze and process insurance claims data in real-time, enabling predictive modeling, fraud detection, and customer retention strategies.- Developed a resilient multi-tier cloud infrastructure on AWS using EC2, RDS, DynamoDB, and S3, and automated deployments with CloudFormation.- Conducted exploratory data analysis and developed predictive models in Python, with real-time insights visualized in Tableau dashboards.- Designed serverless ETL pipelines with AWS Lambda, Glue, and Athena, supporting efficient, on-demand data processing.- Deployed Spark applications in Scala on Google Cloud Platform, optimizing big data processing and reducing batch times by 30%.- Created custom reporting solutions using Python and MySQL, collaborated with Data Warehouse teams on dimensional modeling, and managed CI/CD pipelines with Jenkins, Docker, and Ansible.*Impact*: Improved claims processing efficiency by 50% and reduced fraudulent claims by 20%, enhancing customer satisfaction and data reliability. Show less

- Led Verizon’s customer experience enhancement through big data analytics, consolidating data from various customer interactions to build machine learning models that improved service delivery and satisfaction.- Designed scalable applications for data processing with PySpark, achieving a 40% reduction in processing time through optimized ETL processes.- Worked closely with senior stakeholders to architect data models in AWS Redshift and RDS, ensuring efficient data flow across the… Show more - Led Verizon’s customer experience enhancement through big data analytics, consolidating data from various customer interactions to build machine learning models that improved service delivery and satisfaction.- Designed scalable applications for data processing with PySpark, achieving a 40% reduction in processing time through optimized ETL processes.- Worked closely with senior stakeholders to architect data models in AWS Redshift and RDS, ensuring efficient data flow across the organization.- Implemented rigorous data security protocols, data cleansing, profiling, and monitoring processes to uphold data integrity and compliance.- Extracted and transformed data using Snowflake and SQL queries optimized for AWS Glue, supporting high-performance analytics.- Developed full-stack applications using Python and Django, and automated data ingestion via web scraping routines.*Impact*: Enhanced Verizon’s analytics capabilities, increasing customer satisfaction by 20% and streamlining data workflows. Show less