Hemanth Chesetti

Designed and developed scalable data ingestion and processing pipelines to support account setup and policy creation workflows.

• Designed and implemented scalable data ingestion pipelines for processing policy and account data.
• Developed Python-based document extraction services for efficient processing of structured and unstructured business documents.
• Built event-driven data processing workflows using Apache Kafka for asynchronous communication between microservices.
• Developed REST APIs using FastAPI for data ingestion, validation, and downstream integration.
• Deployed containerized services on Azure Kubernetes Service (AKS) to support scalable and highly available workloads.
• Designed ETL pipelines to cleanse, transform, and load business data into Snowflake for analytics and reporting.
• Implemented data validation, monitoring, logging, and exception handling to improve pipeline reliability and data quality.
• Collaborated with cross-functional teams to deliver cloud-native backend services using Agile methodologies.

Designed intelligent document processing pipelines to automate extraction, validation, and transformation of business documents into structured datasets.

• Developed document processing workflows using WorkFusion and machine learning.
• Built automated data extraction pipelines for processing large volumes of unstructured claim documents.
• Implemented document classification, metadata extraction, and data validation workflows.
• Transformed extracted information into structured datasets for downstream business applications.
• Improved pipeline accuracy and throughput by implementing intelligent extraction and validation logic.
• Generated processing metrics and operational reports for monitoring pipeline performance.

Technologies: Java, WorkFusion, Machine Learning, SQL.

EMEA Claims Data Processing Pipeline

Developed automated data processing workflows for claims document indexing and metadata management.

• Designed workflows to ingest claim documents and associate them with corresponding claim records.
• Processed document metadata, and implemented validation logic before indexing into enterprise applications.
• Automated daily processing metrics and operational reporting.
• Eliminated manual document indexing activities, enhancing overall processing throughput.

Technologies: Java, SQL, and WorkFusion.

Provider Master Data Management Pipeline

Developed automated data synchronization workflows for provider master data management.

• Built Python-based data extraction pipelines to retrieve provider records from SQL databases.
• Performed data validation and reconciliation across enterprise systems.
• Automated creation and update of provider records when inconsistencies are identified.
• Improved master data quality through validation and synchronization workflows.
• Generated audit logs and processing reports for operational monitoring.

Technologies: Python, SQL

SharePoint Data Provisioning Pipeline

Developed automated data provisioning workflows for enterprise document management.

• Designed Python-based workflows to provision SharePoint and network folder structures from Excel-based configuration data.
• Processed and validated input datasets prior to provisioning.
• Standardized folder hierarchy creation through configurable, metadata-driven processing.
• Automated renewal and maintenance workflows to improve operational efficiency.

Technologies: Python, SharePoint, SQL, Excel Automation

• Designed and implemented scalable software solutions to enhance system performance and reliability.
• Led cross-functional teams in Agile development processes, ensuring timely delivery of high-quality software products.
• Mentored junior engineers, fostering skill development and enhancing team productivity through knowledge sharing.
• Analyzed user requirements and translated them into technical specifications for innovative application features.
• Optimized existing codebases, improving efficiency and reducing technical debt across multiple projects.
• Collaborated with product management to define project scope and prioritize feature enhancements based on user feedback.
• Developed automated testing frameworks to increase code coverage and streamline the release process.
• Evaluated emerging technologies to drive strategic decisions that align with company objectives and industry trends.
• Managed multiple projects simultaneously while maintaining strict deadlines and high-quality standards.

Small Group Account Installation – Data Ingestion Pipeline

Developed automated data ingestion and transformation pipelines, enhancing efficiency of employee enrollment processing.

• Built Python-based ingestion pipelines to extract employee and dependent data from FTP repositories.
• Developed ETL workflows to cleanse, validate, and transform enrollment data into standardized formats.
• Integrated processed data with downstream web applications through REST APIs.
• Generated operational reports to improve visibility into data quality and processing performance.

Premium Billing Data Processing Pipeline

Created automated data processing workflows, streamlining premium billing operations and reducing manual efforts.

• Designed Python-based data processing workflows to extract billing work items from enterprise systems.
• Processed, validated, and transformed billing data prior to downstream system integration.
• Automated reconciliation workflows, ensuring data consistency across multiple systems and improving accuracy.
• Reduced manual intervention by automating repetitive data processing tasks.

Technologies: Python, SQL, Automation Anywhere, and Excel.