• 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.• Applied required transformation using AWS Glue and loaded data back to Redshift and S3.• Worked on making REST API (application program interface) calls to get the data as JSON response and parse it.• Experience in analyzing and writing SQL queries to extract the data in Json format through Rest API calls with API Keys, ADMIN Keys and Query Keys and load the data into Data warehouse.• Built data pipeline ETLs for data movement to S3, and then to Redshift.• Implemented ETL pipelines from various Relational Data Bases to the Data Warehouse using Apache Airflow.• Worked on SSIS packages to Extract, Transform and Load ETL data into the SQL Server database from the legacy mainframe data sources.• Worked on Building data DAGS in airflow for ETL related jobs using Python scripting.• Worked on Postman using HTTP requests to GET the data from RESTful API and validate the API calls.• Hands-on experience with Informatica power center and power exchange in integrating with different applications and relational databases.• Prepared dashboards using Tableau to provide visualization to business users from the data.• Created Informatica workflows and IDQ mappings for - Batch and Real Time.• Analysed various type of raw file like Json, Csv, Xml with Python using Pandas, Numpy etc.

• 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.• Analyzed source data coming different sources (SQL Server tables, XML, Flat files etc.,) and transformed according to business rules using Informatica and loaded the data in to target tables.• Involved in creating the Tables and loading the data through Alteryx for Global Audit Tracker.• Analyzed large and critical datasets using HDFS, HBase, Hive, HQL, PIG, and Sqoop.• Worked on Google Cloud Platform (GCP) services like compute engine, cloud load balancing, cloud storage and cloud SQL.• Changing the existing Data Models using Erwin for Enhancements to the existing Datawarehouse projects.• Used Talend connectors integrated to Redshift – BI Development for multiple technical projects running in parallel.• Created iterative macro in Alteryx to send Json request and download Json response from webservice• Experience in Google Cloud components, Google container builders and GCP client libraries.• Supported various business teams with Data Mining and Reporting by writing complex SQL queries using OLAP functions like ranking, partitioning and windowing functions, Etc.

• 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 organizations to integrate data from diverse systems and platforms.• 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.• Integrated on-premises (MYSQL, Cassandra) and cloud data (Blob storage, Azure SQL DB) using Azure Data Factory and applied transformations for loading into Snowflake.• Deployed Data Factory to create data pipelines for orchestrating data into SQL databases.• Modeled data in Snowflake using data warehousing techniques, performed data cleansing, managed Slowly Changing Dimensions, assigned surrogate keys, and implemented change data capture.• Utilized Azure Data Factory, Data Lake, and Azure Synapse to solve business problems with an analytical approach.