Meghana Gonuguntla

To associate with an organization that provides me an opportunity to show my techno-proficient skills, to improve my knowledge with the latest trends and to be a part of the team that works dynamically towards the growth of the organization.

4 years of experience in cloud data warehousing projects in AWS and Azure Platforms. Proficient in designing, implementing, scheduling and monitoring data pipelines and data warehousing solutions. Experience working with AWS and Azure, including services such as S3, Redshift, Azure Data Lake, and Azure Data Factory, Azure SQL Pools. Proficient in using Databricks for big data processing and analytics, including cluster management, notebook development, and Spark-based data manipulation. Experience in creating, scheduling and monitoring Databricks workflows. Proficient in Relational Databases like Oracle, MySQL. Experience in Informatica Power Center. Hands on experience in deploying codes into GitHub. Strong knowledge on Agile development methodologies, ensuring timely delivery of high-quality data solutions.

• Little Fuse, Retail, Little fuse is an electronic manufacturing company. It produces circuit protection products but also manufactures a variety of electronic switches and automotive sensors., Cost management for the VM in the Dedicated SQL pool., Creating of pipelines in the ADF in which it will be useful for the cost reduction in the Dedicated SQL., Cost management for the VM in the Dedicated SQL Pool., Will be working on Storage accounts as part of cost analysis.
• TMNA NDW, Automobile, Toyota Motors North America is the operating subsidiary that oversees all operations of the Toyota Motor Corporation in Canada, Mexico, and the United States. Here NDW Modernization program is uplifting the data warehouse from on-prem to cloud. Implementing delta lake house with the same functionality which was developed by Informatica and Oracle in the cloud using Databricks SQL, stored in Redshift. Later reporting team will apply the queries based on pre-created views in the Tableau platform. Those report insights are useful for the client to forecast and faster decision making., Converting Informatica mappings into Databricks SQL queries or views., Loading history data and incremental using Scala scripts., Validating and reviewing the SQL code in the notebooks as per mappings., Creating Hocons/Config files for the code which is developed using notebooks., Deploying config files in GitHub by creating pull requests., Creating workflows in Databricks and running the jobs., Creating audit entries for log tables., Creating tasks and plans in Talend Management Console and Scheduling the jobs based on the triggers in TMC., Validating incremental loads and data quality checks.

I hereby declare that the above written particulars are best of my knowledge and belief.

Quantum, Retail, Quantum Project is a Sap migration project in which the data will loaded in to the sap data model and the end users uses it., My role in this project is tester., Will be doing the DQ checks for the data after the data is loaded into the staging tables.

AWS, AZURE, S3, Redshift, Informatica, Databricks SQL, Azure Data Factory, Azure SQL pools, Azure storages, SQL, Oracle, MySQL, TMC, Stonebranch, ADF, GitHub