Anjaligupta Raghavendra

Experience

1. Data Engineer

   Optum

   Jan 2024 — Present · US

   Designed and maintained scalable ETL pipelines using Azure Data Factory (ADF) to ingest Claims, Provider, Member, and Benefits data from SQL Server, SFTP, and REST APIs into Azure Data Lake Storage (ADLS Gen2)• Developed transformation workflows in Azure Databricks (PySpark) to cleanse, standardize, deduplicate, and enrich multi-million record healthcare datasets• Built dimensional data models (Fact & Dimension tables) in Azure Synapse Analytics (Dedicated SQL Pool) using star schema design to support finance, actuarial, and provider analytics reporting• Optimized Synapse performance using partitioning, clustered columnstore indexes, query tuning, and statistics management, improving query speed by 30%+• Developed automated data validation and reconciliation checks using Python and SQL (row counts, null checks, schema validation, business rules)• ⁠Implemented CI/CD pipelines using Azure DevOps, ARM templates, and Git, enabling automated deployments across Dev, QA, and Prod environments• Built and deployed a multi-modal RAG medical equipment chatbot using Azure OpenAI, and FastAPI implementing prompt engineering experiments that improved technician equipment lookup time by 35%• Supported a Text-to-SQL Copilot using fine-tuned LLaMA2-7B (LoRA) to enable non-technical users to query enterprise healthcare data, reducing manual SQL development time by 65%• Configured monitoring, alerting, and secure data access using Azure Monitor, Log Analytics, RBAC, Azure AD, Managed Identities, Encryption, and Azure Key Vault, ensuring HIPAA compliance and improved SLA adherence• Collaborated with BI developers and analysts to deliver curated datasets for Power BI dashboards and enterprise reporting

Education

• New Jersey Institute of Technology

  Master of Science - MS

  2023 — 2025

• VIDYA VIKAS INSTITUTE OF ENGINEERING AND TECHNOLOGY

  Bachelor of Engineering - BE

  2018 — 2022