
UDAY SRIDHAR REDDY BEERAM
@udaysridharreddybeer
I build scalable Azure and AWS data platforms that turn millions of records into trusted analytics.
What I'm looking for
At Intuit, I build cloud-native ETL/ELT pipelines that process 25M+ financial records daily, reducing manual preparation by 30% and supporting enterprise analytics.
I architected a Microsoft Fabric and Azure Synapse Lakehouse with Delta Lake and Medallion Architecture, improving data reliability and reducing dashboard refresh latency by 40%. I also tune PySpark and SQL workloads, cutting large-scale query execution from 45 seconds to under 12 seconds.
Previously at Infosys, I engineered Azure-based healthcare data pipelines processing 8M+ records daily and organized 15 TB of data into trusted analytics-ready datasets. My work improved data quality, accelerated reporting, and strengthened validation, reconciliation, and schema enforcement across source systems.
I enjoy turning structured and semi-structured data into reliable datasets, dimensional models, and Power BI reporting that help finance, healthcare, and business teams make data-driven decisions.
Experience
Work history, roles, and key accomplishments
Engineered scalable ETL/ELT pipelines using Azure Data Factory, PySpark, Azure Databricks, and ADLS Gen2 to process 25M+ financial records daily. Architected a cloud-native Lakehouse using Microsoft Fabric and Medallion Architecture, improving data reliability and reducing dashboard refresh latency by 40%.
Engineered scalable ETL pipelines using Azure Data Factory, Python, PySpark, Azure Databricks, and ADLS Gen2 to process 8M+ healthcare records daily. Implemented Medallion Architecture and optimized query performance, improving data quality and enabling reliable reporting for 300+ users.
Education
Degrees, certifications, and relevant coursework
George Mason University
Master of Science, Data Analytics Engineering
Pursued a Master's degree in Data Analytics Engineering, completing in May 2025.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Job categories
Skills
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