Pranay Reddy

About Pranay Reddy

Passionate and results-driven Data Engineer with 5+ years of experience in designing, building, and optimizing cloud-based data solutions using Azure, AWS, and GCP. Skilled in Big Data technologies, ETL processes, and Data Warehousing, I specialize in Azure Data Factory, Databricks, Snowflake, Synapse Analytics, and Spark to drive enterprise-wide analytics and business intelligence. My expertise spans SQL, Python, Scala, Kafka, and Power BI, enabling me to deliver high-performance data architectures and actionable insights.

Experience

1. Azure Data Engineer

   CVS Health

   Nov 2022 — Present · Dallas, TX, US

   Leveraged Azure Data Factory, Data Lake, HDInsight, Synapse Analytics, Cosmos DB, and Databricks for comprehensive data analysis and management within a Big Data framework.• Worked with the analysis teams and management teams and supported them based on their requirements• Migrated SQL databases to Azure platforms using DDL statements and configured Linked Servers for data transfer between SQL servers.• Developed Spark applications in Databricks for data extraction, transformation, and aggregation, enhancing ETL processes.• Utilized Python, PySpark and Linux Shell scripting for data loading, transformation, and integration efforts, ensuring seamless workflow.• Automated cluster creation in Azure HDInsight’s with PowerShell scripts, streamlining deployment processes. • Designed, developed, and maintained scalable data pipelines using AWS services such as EMR, Glue, and Redshift to support real-time analytics.• Implemented data lake solutions on AWS S3, integrating data from multiple sources for big data analytics and machine learning models.• Orchestrated batch and real-time data processing using Apache Spark on AWS EMR, improving data processing speeds by 40%.• Developed server less data processing solutions using AWS Lambda and Kinesis, enabling near real-time data streaming and analytics.• Continuously monitor and manage data pipeline (CI/CD) performance alongside applications from a single console with Azure Monitor. • Designed and deployed production-grade data solutions on platforms like Snowflake Data Warehouse and Azure Data Lake, enhancing data analytics capabilities.• Data Ingestion to one or more Azure Services -(Azure Data Lake, Azure Storage, Azure SQL, Azure DW) Informatica and processing the data in In Azure Databricks.

Education

• Pace University

  Master's degree

  2022 — 2024

• Sri Vidyaniketan Engineering College, Tirupathi,

  Bachelor of Technology

  2015 — 2019