Charishma R

About Charishma R

I’m a Senior Data Engineer with several years of experience in healthcare, finance, and…

Experience

1. Senior Big Data Engineer

   Walgreens

   Oct 2022 — Present

   At Walgreens, I played a key role in architecting and implementing a real-time supply chain analytics platform leveraging Apache Druid, Kafka, and Azure services. The project aimed to provide instant visibility into inventory flow, supplier responsiveness, and transportation timelines—enabling data-driven decisions at scale.To support low-latency analytics, I deployed Apache Druid in a production-grade environment, tuning middle managers, historical nodes, and ingestion specs to ensure high throughput and fault tolerance. I configured real-time ingestion pipelines using the Kafka indexing service in Druid, allowing ingestion of millions of events per day with sub-second query response times.The platform consumed streaming data from POS systems, vendor APIs, and logistics signals via Apache Kafka and Pulsar. I worked on designing Druid data schemas, segment granularity, and partitioning strategies to optimize both storage footprint and query performance. I also fine-tuned query execution by adjusting query context, caching layers, and indexing policies.On the transformation side, I used Azure Data Factory and Databricks (Scala and PySpark) to enrich raw datasets and publish to both Druid and Synapse Analytics for combined real-time and historical trend analysis. Delta Lake was used to maintain historical snapshots and ACID-compliant transformations.To drive adoption, I built Power BI dashboards with real-time insights on vendor SLAs, shipment delays, and replenishment forecasting, enabling supply chain stakeholders to take immediate corrective action.The solution was tightly integrated with Azure Key Vault, RBAC, and CI/CD via Azure DevOps, ensuring governance, security, and scalability. This initiative improved demand planning accuracy by 25%, reduced out-of-stock events, and gave retail leadership unprecedented visibility into end-to-end supply chain performance.