Data Engineer at PNC Financials

Designed and implemented serverless data pipelines using AWS Lambda, API Gateway, and DynamoDB to enable real-time ingestion and processing of structured and unstructured data from S3 events. Built ETL jobs with AWS Glue and PySpark to transform data from S3 (ORC/Parquet/Text) into Redshift, improving analytical insights and reducing manual intervention. Developed AWS Step Functions workflows integrated with Lambda, SQS, and DynamoDB to manage stateful data processing and scale pipelines. Created CloudFormation templates to automate provisioning of AWS resources (S3, RDS, EC2, IAM, SNS, SQS), ensuring reproducibility and adherence to infrastructure-as-code practices. Utilized AWS Athena and Hive to perform interactive queries on S3-based datasets and developed external table partitions for optimized big data analysis and reporting. Performed data modeling and schema design in Redshift to support high-performance querying and reporting. Implemented AWS CloudWatch to monitor Lambda execu

Data Engineer at CVS Health

Collaborated with cross-functional teams to develop predictive models using Random Forest, SVM, Neural Networks, and Logistic Regression to address customer churn, retention, and personalized recommendations on Microsoft Azure. Achieved customer retention uplift by implementing churn prediction models for targeted marketing strategies. Conducted geospatial analysis & visualization using Pandas, Matplotlib and Tableau to uncover location-based customer behavior trends. Applied NLP techniques using Python and NLTK to classify and extract sentiment from Foursquare online reviews for customer experience analysis. Designed and evaluated content-based and collaborative filtering recommendation systems using Apache Spark with Scala on Databricks and AWS to enhance movie recommendation accuracy and scalability.