End-to-End Financial Data Pipelines & AI Automation

• Designed high-performance ETL systems processing 10M+ daily records from SFTP, APIs, and PDFs using Python/AWS AppFlow

• Automated 70% of financial document processing with AWS Bedrock NLP, improving data accuracy by 60%

• Reduced pipeline latency 30% by implementing Airflow with parallel Lambda workflows for Snowflake/RDS ingestion

• Transformed raw financial data into analytics-ready models using DBT, increasing reporting reliability by 25%

AI-Powered Document Intelligence

• Developed ML classification system that reduced manual PDF sorting by 70% (prospectuses, contracts, statements)

• Built automated Snowflake mapping pipelines that enabled dashboard integration within 1 day (vs 3 days manual)

Data Governance & Stakeholder Analytics

• Launched secure QuickSight dashboards with RLS/Cognito auth, cutting audit processing time by 35%

• Created Tableau visualizations that influenced $500M+ investment decisions through improved risk visibility

Cloud Infrastructure Optimization

• Slashed Athena query costs 35% through partitioning strategies and Glue catalog optimizations

• Automated database deployments with Flyway, reducing production incidents by 50%

• Doubled data throughput by optimizing S3-Lambda-PostgreSQL pipelines with smart partitioning

Leadership & Innovation

• Mentored 3 junior engineers through code reviews and project delegation

• Championed adoption of AI document processing across 5+ business units

• Established data quality standards that reduced reporting errors by 40%

• Designed and developed data pipeline using Azure Functions to ingest medical data from Redox and EMR services into Data Lake container.

• Utilized Azure Queue to listen for new data and trigger pipeline execution.

• Cleaned and normalized raw data, flattening nested JSON files into tabular form using Python libraries such as pandas and NumPy.

• Stored cleaned data in Data Lake or databases such as Azure SQL or Cosmos DB for further processing and visualization.

• Designed and implemented an Azure data batch and CDC pipeline to ingest files from an SFTP location, perform ETL to clean and process the data, store it in a Data Lake, and visualize it in Power BI, resulting in a 20% reduction in response time.

• Created an expedited data migration pipeline to transfer 50GB of data from an on-premises data warehouse to the cloud, simplifying cloud migration at scale.

• Optimized real-time data pipelines for PostgreSQL, Oracle, MySQL, and MS SQL with 87% optimization.

• Developed solutions and built data analytics models around a variety of sales and

marketing problems of US-based pharmaceutical, biotech, and medical product clients.

• Supervised and managed the end-to-end responsibility and took overall ownership of

the solution delivery of more than 10 projects across all phases from discovery,

requirements gathering, design, implementation, testing & operations.

• Python Widgets: Developed and built python widgets and scheduler for automating the

complete data cycle which increased the efficiency of the process by 10% for multiple

clients.

• Web Scraper: Designed a web scraper to automate the process of traversing the opensource website to do specific tasks and download the data automatically

• Forecasting tool: Created a forecasting tool that lets the client select the features, that

analyses the data and spits out different forecasts

• Collaborated in the agile development of project timelines, system flow diagrams,

documentation, testing, and ongoing support of systems with expertise in the development

of tech-enabled solutions in VBA, Python.

• Built sustainable relationships and trust with customer accounts using open and

interactive communication.

• Assisted with new hire orientation and employee training.