Cloud AI Engineer at JPMorgan Chase

Orchestrated the migration of substantial data volumes from AWS S3 to Redshift using Glue and EMR for efficient data processing. Collaborated with ML engineers to build AI-powered solutions, including conversational chatbots, RAG pipelines, and embedding workflows using Bedrock, Titan models, SageMaker JumpStart, and SageMaker Pipelines. Designed Retrieval-Augmented Generation frameworks combining Amazon Kendra with Bedrock-hosted LLMs for dynamic responses. Implemented vector embeddings, monitored vector ingestion and API latency with Splunk integration, and deployed scalable data pipelines powering GenAI and ML platforms. Built chatbot experiences using Amazon Lex, Comprehend, and Bedrock and configured containerized deployments with Amazon ECS. Established CI/CD pipelines, Terraform-based infrastructure provisioning, and real-time monitoring with CloudWatch and Lambda.

Data Engineer at Bank of America

Led data engineering initiatives to migrate on-premises and cloud data assets to AWS services, enabling scalable analytics with S3, Redshift, RDS, and Glue. Built AI-powered features including RAG workflows, embedding pipelines with FAISS, and GenAI integrations using Bedrock, Titan, and SageMaker JumpStart. Implemented Retrieval-Augmented Generation using Kendra for semantic search and integrated monitoring with Splunk for vector ingestion and API latency. Designed and deployed scalable data pipelines powering real-time insights and dashboards, and automated infrastructure using Terraform and ECS.

Big Data Engineer at S&P Global Market Intelligence

Developed batch and streaming data pipelines using S3, Glue, EMR, Spark, and Hadoop to ingest, transform, and distribute data to Redshift and Snowflake. Created Apache Airflow DAGs and Step Functions to orchestrate workflows; built data models and data warehouses; implemented PySpark transformations; deployed containerized workloads with Kubernetes and Docker; set up monitoring with CloudWatch and ElasticSearch; collaborated with analytics teams to translate business needs into scalable data delivery solutions.

Data Analyst at HP

Supported enterprise data initiatives as a Data Analyst by gathering, cleaning, and transforming data; building dashboards and reports for stakeholders using Power BI, Tableau, or Looker; writing complex SQL across PostgreSQL, MySQL, Redshift, and BigQuery; performing exploratory data analysis, identifying KPIs, and assisting with predictive and descriptive modeling; improving data pipelines and promoting data-driven decision making; ensuring GDPR/CCPA compliance.

SQL Developer at Nationwide

Worked as SQL Developer in BI/Data Warehouse initiatives; designed and implemented ETL processes using SSIS, SSAS, SSRS; developed dimensional models (facts and dims) including SCD; built and deployed cubes, MDX queries, and dashboards; established data governance, data quality, and documentation; collaborated with stakeholders to translate business requirements into technical data solutions.

Cloud AI Engineer at JPMorganChase

Led data engineering efforts for cloud-based AI initiatives, orchestrating scalable data workflows across AWS services including S3, Glue, and EMR. Migrated data assets to Redshift and integrated AI/ML workloads using Bedrock, Titan models, and SageMaker pipelines to enable rapid experimentation and production-ready AI solutions.

Data Engineer at Bank of America

Member of Enterprise Data Enable Analytics team; built batch and streaming data pipelines on GCP (BigQuery, Vertex AI, AlloyDB); developed monitoring solutions using Google Cloud Monitoring and Logging; optimized data models in Power BI and authored complex SQL queries for analytics.

Big Data Engineer at S&P Global Market Intelligence

Platform Enhancement team responsible for building self-service applications and self-service batch and streaming pipelines using cloud services; contributed to ETL and data warehousing efforts.

Data Analyst at HP

Supported enterprise data initiatives by analyzing large datasets; created dashboards; wrote SQL; collaborated with stakeholders; ensured data governance and quality.