Vishal Chintapally

About Vishal Chintapally

I am a Senior Data Engineer with over 7+ years of experience building scalable, high-performance data pipelines and cloud infrastructure within the healthcare and logistics sectors. My expertise lies in architecting end-to-end data solutions using Databricks, PySpark, and AWS/Azure to transform complex raw data into actionable business intelligence.Currently, at Cigna Healthcare, I focus on optimizing large-scale data processing and troubleshooting complex system challenges to ensure reliability and efficiency. I am passionate about leveraging Big Data technologies to solve intricate problems and am always looking for ways to streamline data flow and architecture.

Experience

1. Senior Data Engineer

   Cigna Healthcare

   Dec 2022 — Present · Bloomington, MN, US

   Project Deep Dive: DaaS (Data as a Service)Team: Intelligence SolutionsRole: Senior Data Engineer / Technical LeadExecutive OverviewThe DaaS (Data as a Service) initiative was a flagship project within the Intelligence Solutions team, designed to monetize internal data assets by providing high-fidelity, actionable analytics to external clients. My role centered on building the \"bridge\" between our legacy Information Warehouse and a modern, cloud-native ecosystem. By migrating on-premises PySpark pipelines to AWS/Databricks, I transformed a bottlenecked legacy system into a high-throughput revenue engine that empowers our Business Intelligence (BI) teams to deliver premium insights to the market.Architectural Evolution: From On-Prem to CloudThe core challenge was the transition from a traditional on-premises infrastructure to a scalable AWS/Databricks environment.Migration Strategy: I contributed to the re-architecting of legacy PySpark pipelines, moving away from local cluster constraints to the elastic scalability of Databricks. This involved optimizing jobs to utilize Delta Lake for ACID transactions and improved reliability.Upstream Integration: I managed the complex ingestion layer where data originated in the Information Warehouse, processed via Ab Initio. I ensured that the hand-off between Ab Initio and our cloud environment was seamless, maintaining data lineage and integrity throughout the hop.Infrastructure as Code & CI/CD: To ensure the migration wasn\'t just a \"lift and shift,\" I integrated CI/CD processes that automated testing and deployment. This ensured that any change to the DaaS pipeline was validated before hitting production, drastically reducing downtime.Performance Tuning: By leveraging PySpark optimization techniques—such as broadcast joins, partitioning strategies, and caching. I reduced processing windows, ensuring that downstream BI teams received their data \"fresh\" every morning for client delivery.

Education

• University of Oklahoma

  Master of Science, Computer Science