Ankitha S Email & Phone Number

Austin, TX, US

Austin, Texas, United States

• Worked on Design, Development and Documentation of the ETL strategy to populate the data from the various source systems using Talend ETL tool into Data Warehouse.
• Developed Python scripts to parse XML, Json files and load the data in AWS Snowflake Data warehouse.
• Worked on ETL processes in AWS Glue to migrate data from S3 to AWS Redshift.
• Worked on Data Warehousing, Business Intelligence and ETL process (Informatica)
• Experience in working with large data sets and analysis
• Validated and deployed the Talend ETL processes for the Data Warehouse team using Hive.

Irving, TX

• Performed Data Analysis, Data Migration, Data Cleansing, Transformation, Integration, Data Import, and Data Export.
• Involved in Business Requirements Analysis, preparation of Technical Design documents, Data Analysis, Logical and Physical database design, Coding, Testing, Implementing, and deploying to business users.
• Used SSIS to populate data from various data sources, creating packages for different data loading operations for applications.
• Performed migration to move Data Warehouse from an Oracle platform to AWS Redshift.
• Built S3 buckets and managed policies for S3 buckets and used S3 bucket and Glacier for storage and backup on AWS.
• Developed complex mappings using Informatica Power Center Designer to transform and load the data from various source systems (Oracle, Teradata etc.,) into the final target database.

Hyderabad, Telangana, India

• Developed and maintained end-to-end operations of ETL data pipeline, handling large datasets in Azure Data Factory.
• Implemented optimized queries and indexing techniques to enhance data fetching efficiency.
• Wrote SQL queries (DDL, DML) and implemented indexes, triggers, views, stored procedures, functions, and packages.
• Build and managed ETL workflows and pipelines to extract data from multiple sources, perform transformations, and load it into desired destinations.
• Worked on Azure Data Factory connectors to connect to various data sources and destinations, including on- premises databases, cloud-based storage, software-as-a-service (SaaS) applications, and more. This allows.
• Involved in data transformation capabilities to clean, enrich, and shape the data during the ETL process. These transformations can be performed using activities like mapping, filtering, aggregating, joining, and more.