Yamuna G K

To Secure a responsible career opportunity to fully utilize my training and to improve my knowledge and skills. To work in an active environment while making a significant contribution to achieve mutual growth.

Have 4.3 years of experience in IT industry and 3.9 year of Experience as an ETL Developer and data migration developer. Worked in DXC Technology as an Engineer for 6 months. Good team player with good communication (Verbal and Technical). Proficient in performing unit testing and data movement from raw to cleansed layer. Experience in Data cleansing and Data Transformation. Worked in Azure Data Lake for Data Migration, Azure Data Factory for building pipelines, Azure Databricks for SQL & Pyspark notebooks. Trained in Azure Cloud Services (ADF, Azure Storage, Databricks) and mentored by industry experts.

• Azure AZ-900
• AWS Certified Cloud Practitioner
• Azure DP-900

Kellogg's NGA(May 2021 - April 2022)

• Kellogg'sNGA_KeyStone2.0 objective is to move data from different source system to AWS cloud for tableau analytics.
• Worked on AWS cloud environment to move data from raw layer to cleansed layer. Performed data transformation and Data cleansing. Used various technologies like AWS S3, AWS Glue, AWS Cloud Watch and AWS Cloud Transformation.
• Created Glue Jobs to move the data from one layer to another. Executed Unit Testing on the data.

MDIP Application migration (Jun 2022 - Present)

• Teradata to Synapse Migration: Within 5 months' timeframe, I successfully migrated 3 applications Involving 270+ objects with its history data and incremental load logic development.
• To pull the data from Teradata we will using S&T framework. Once data is available in bronze layer then transformation is performed on bronze data and will be loaded into silver layer, Transformation logic is implemented using pyspark in azure databricks platform. then data is harmonized from silver to gold layer. These delta tables is referenced as external table in azure synapse (SQL server) and store procedure is used to load the permanent.
• Overall, the deliverables for the Teradata to Synapse migration aim to successfully transfer the data, maintain data integrity, optimize performance, and ensure a smooth transition to the new analytics environment.
• Roles and Responsibilities: Converting pyspark scripts and reading the data in the notebooks and implementing incremental logic. Creating external tables and internal tables. Using store procedure will push the data from external to internal tables. On top of internal tables will create views. Migration of on-premises data (Teradata) to Azure data lake store(ADLS) using Azure Data factory Performance Optimization, Documentation and Knowledge Transfer, Post-migration Support.
• Discovery and Analysis: Thoroughly explored the 375+ existing scripts used in Teradata. Understood their purpose, functionality, and dependencies. Identified the tables, views, stored procedures, and other database objects involved in the data migration process. Compatibility Check: Assess the compatibility of the existing Teradata scripts with the Synapse environment. Consider differences in syntax, data types, functions, and features between Teradata and Synapse. Identify any unsupported features or functionalities that need to be addressed during the migration.

• Date of Birth: 06/10/98
• Gender: Female
• Nationality: Indian
• Marital Status: Single

• English
• Kannada
• Telugu

• Azure Data fundamentals(DP-900)
• Azure fundamentals(Az-900)
• AWS Cloud Practitioner