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Mayuri Raut

@mayuriraut

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Azure Data Engineer at TCS who built real-time financial data pipelines and risk analytics platforms.

India

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At TCS, I worked on a real-time financial data pipeline and risk analytics platform, developing Azure Data Factory ETL/ELT pipelines and stream-processing logic using Stream Analytics and Kafka. The platform processed financial transactions, market data, and risk metrics for real-time analysis and compliance reporting.

I also designed a HIPAA-compliant healthcare lakehouse on Azure Synapse and ADLS Gen2, with Delta Lake pipelines on Databricks and automated data governance. The project reduced 30-day patient readmissions by 22% and analytics query latency by 60% across 15M+ patient records.

Experience

Work history, roles, and key accomplishments

Azure Data Engineer

TCS

Feb 2022 - Sep 2025 (3 years 7 months)

Built an enterprise-grade real-time data pipeline for financial transactions, market data, and risk metrics, with sub-second latency and ML-based anomaly detection. Implemented stream processing with Stream Analytics and Kafka, and optimized Synapse Analytics query performance.

Azure Data Factory Azure Stream Analytics Azure Cosmos DB Azure Synapse Azure SQL Database Power BI Python Apache Spark Event Hub Key Vaults Azure Monitoring

Healthcare Data Engineer

TCS

Feb 2022 - Sep 2025 (3 years 7 months)

Architected a HIPAA-compliant healthcare data lakehouse on Azure Synapse and ADLS Gen2, unifying EHR, imaging, claims, and genomics data. Implemented Delta Lake pipelines on Databricks and delivered MLOps pipelines in Azure Machine Learning, reducing 30-day readmissions by 22%.

Azure Synapse Data Lake Storage Gen2 Databricks Azure Machine Learning Delta Lake Apache Spark Python Azure Key Vault Azure Policy Purview

System Engineer

TCS

Feb 2022 - Sep 2025 (3 years 7 months)

Designed and delivered scalable Azure data solutions, including real-time financial data pipelines and risk analytics platforms. Architected ETL/ELT pipelines using Azure Data Factory and Databricks, processing 5TB+ daily and reducing data latency by 45%.