Manikanta Kotla

Project Name: Travelers Insurance systems

Project Description: client is an us based Multi purpose insurance provider and provides institutional , Pet and Travel along with Umbrella insurance through financial advisors, brokers, and direct marketing channels For nearly 171 years, Customers have put their trust in the financial strength of the companies Today, the company serve approximately 10 million customers in the Americas, Asia Pacific and Europe To provide best services for their long-term customers, they have been analyzing business information by data warehousing applications and migrating native on-premises to Transaction Db's like Salesforce

• Collaborated with business analysts and product owners to understand database and Transaction requirements
• Designed ETL processes using Azure Data Factory for seamless data extraction, transformation, and loading from oracle to Salesforce
• Created linked services, Datasets and pipelines and triggers in Data Factory
• Implemented delta lake Architecture for Analysis Purpose and other ML requirements in ADLS and Azure SQL database.

Stack: Azure Data Factory, Azure SQL, Oracle, Azure DevOps, Salesforce, ADLS Gen 2

Project Name: US Data Strategy

Project Description: The client is Multinational Banking and Financial Service Provider based in Toronto, Ontario The client is committed to protecting the safety, soundness, and reputation of the Client by reducing the likelihood that the Client will be used as a vehicle for, or become a victim of, Money Laundering or Terrorist Financing (ML/TF) activities

• Interacted with Business analysts in understanding the Database requirements whenever debugging is required without changing the code
• Extensively Identified and created reusable pipelines using Talend Data Fabric
• Designed ETL processes using Talend Data Fabric to load data from the source system (Database tables) and Data Transformations and then load to the Z0 Target (Database tables)
• Preparation of Flow diagrams / Project diagrams and Enhancement Documentation
• Designed Azure Data Factory Pipelines to load data from Databases to ADLS Blobs
• Performed Data Profiling and Masking Techniques for the secrecy of data using Talend
• Created Tables, Metadata, Audit tables, and dependency Tables using Azure SQL
• Worked on Azure data bricks, HDInsight, and Azure ADF for loading and transforming data from Azure SQL to ADLS
• Orchestrated all Data pipelines using Azure Data Factory and built a custom alerts platform for monitoring
• Prepared SIT/UAT/Production Deployment Documentation
• Created Azure Blobs data sets and pipeline copy activities using Python
• Deployed code from Dev to SIT/UAT/Production by Azure DevOps
• Executed TAC/JASON/SQL Pipelines using Azure DevOps
• Prepared Design/Mapping document
• Assisted in production deployment and provided KT to the production team
• Executed unit testing and worked on performance tuning of the Jobs
• Analyzed session error logs and fixed bugs in the development by following change procedures and validation
• Precisely documented mappings to ETL Technical specification documents across all stages
• Client Communication; Sustenance, and requirement gathering from Onsite Team

Stack: Talend Data Fabric 7.3.1, Azure Data Factory, Databricks, Azure SQL, Oracle, Python, TAC, Autosys, Azure DevOps

Project Name: Majestic

Project Description: Randstad is a Dutch multinational HR consulting firm founded in 1960, headquartered in Diemen, Netherlands With 4,400+ branches worldwide and 29,000+ employees, it operates core systems on IBM WebSphere and DB2 Functions include candidate management, client management, and SPOT management for short-term assignments, contract billing, and payroll Currently, Randstad seeks to integrate employee staffing and billing/payment functionalities into Salesforce

• Worked with Business Analysis team in gathering the requirements and created Functional and ETL specification documents
• Analyzed the Data Set and Field Definition Document and laid out the steps for the data extraction, business logic implementation & loading into targets
• Need to analyze the STM (source to target mapping) from data analyst team and do the validation to start the mappings
• Implementing Azure Data factory pipeline components such as linked services, Datasets and Activities
• Involved into end to end Development, Implementation & production support process from dev to prod environment

Stack: Azure Data Factory, Synaps, Azure SQL, Oracle, jira