Sitaramaraju Mudunuri Email & Phone Number

Austin, Texas Metropolitan Area

Contributed to gathering requirements, analyzing the entire system, and providing development and testing effort estimations. Participated in designing various system components such as Sqoop, Hadoop (including MapReduce and Hive processes), Spark, and FTP integration with downstream systems. Crafted optimized Hive and Spark queries utilizing techniques like window functions and customizing Hadoop shuffle and sort parameters. Developed ETL processes using PySpark, leveraging both Dataframe API and Spark SQL API. Utilized Spark for diverse transformations and actions, with final result data saved to HDFS and then to the target database Snowflake. Orchestrated the migration of an existing on-premises application to AWS, utilizing services like EC2 and S3 for processing and storing small datasets, and maintaining Hadoop clusters on AWS EMR. Demonstrated expertise in real-time data analytics employing Spark Streaming, Kafka, and Flume. Configured Spark streaming to capture ongoing information from Kafka and store it in HDFS. Designed and implemented ETL processes in AWS Glue for migrating Campaign data from external sources to AWS Redshift. Employed various Spark transformations and actions for data cleansing. Utilized Jira for issue tracking and Jenkins for continuous integration and deployment, enforcing data catalog and governance best practices.

Houston, Texas, United States

Develop, plan, and construct contemporary data solutions that facilitate data visualization by utilizing Azure PaaS services. Determine how a new implementation will affect the present business processes by understanding the current state of application in production. Using a combination of Azure Data Factory, T-SQL, Spark SQL, and U-SQL, extract, transform, and load data from source systems into Azure Data Storage services Azure Analytics Data Lake. Data is ingested into Azure Services (Azure Data Lake, Azure Storage, Azure SQL, and Azure DW) and processed in Azure Databricks. Prototypes for SOAP and REST APIs were implemented. Obtain analytics data from various data feeds via REST APIs Designed DynamoDB schemas and data models to optimize performance, scalability, and cost-effectiveness for various use cases and workloads.

Houston, Texas, United States

In my capacity as the Snowflake Database Administrator, I oversaw the design of the data model, the deployment of production releases for the database migration, and the successful implementation of the corresponding metadata into the production platform environments on the AWS Cloud (Dev, Qual, and Prod). Managed daily integration with the DB2, SQL Server, Oracle, and AWS Cloud teams of database administrators (DBAs) to guarantee that database tables, columns, and associated metadata were successfully inserted into the Aurora and Snowflake environments in the DEV, QUAL, and PROD regions of AWS Cloud. Converted functional requirements from source to target data mapping documents using Informatica for ETL data translation, supporting big data projects involving massive datasets (such as Snowflake and Aurora) in AWS Cloud databases.

Analyzed the business requirements and framing the Business Logic for the ETL Process and maintained the ETL process using Informatica PowerCenter 10.4.0 Worked on Agile Methodology, participated in daily/weekly team meetings, worked with business and technical teams to understand data and profile the data. Understanding transformation and techniques especially with prem source to Attunity. Expert in designing Parallel jobs using various stages like Join, Merge, Lookup, remove duplicates, Filter, Dataset, Lookup file set, Complex flat file, Modify, Aggregator, XML. Update Strategy, Aggregator, Expression, Joiner Transformations and then loaded into data Warehouse using Informatica BDM 10.2.