Manish Sagar Damani Email & Phone Number

Schaumburg, Illinois, United States

Chicago, Illinois, United States

•Initiated CI/CD processes using Azure DevOps to automate routine tasks and ensure efficient software deployment.•Leveraged Talend Data Integration and Big Data technologies to perform data integration across several databases and the Apache Hadoop System, which is made up of HDFS, Hive, and HBase. •Supervised the development and maintenance of applications using Azure services and tools, using Azure Functions for serverless computing; organized data workflows and ETL processes with Azure Data Factory, with a focus on seamless data integration across various sources and destinations.•Extracted valuable insights from large datasets through big data analytics and machine learning.

Chicago, Illinois, United States

•Oversaw the creation of Linked Services for multiple source system (i.e., Azure SQL Server, ADLS, BLOB, Rest API) and pipelines to extract data from on premises source systems to Azure cloud data lake storage.• Participated in copy activities and implemented the copy behavior’s such as flatten hierarchy, preserve hierarchy and Merge hierarchy; implemented Error Handling concepts through copy activity.•Garnered experience with Azure Data Factory activities such as Lookups, Stored Procedures, If Condition, For Each, Set Variable, Append Variable, Get Metadata, Filter, and Wait.•Orchestrated the configuration of logic apps to handle email notification to the end users and key shareholders with the help of web services activity.•Constructed a dynamic pipeline to handle multiple sources extracting to multiple targets; extensively employed Azure key vaults to configure the connections in Linked Services.

Hyderabad, Telangana, India

•Established the process to ingest data coming from various source databases to Hadoop using Sqoop.•Produced Hive tables for loading and analyzing data; implemented Partitions and Buckets; devised Hive queries to process the data and generate the data cubes for visualizing.•Integrated custom aggregate functions using Spark SQL; conducted interactive querying.• Employed Spark SQL context to create data frames to filter input data for model execution.•Demonstrated proficiency with file formats like Text, Sequence, Avro, Parquet, ORC, JSON, XML, and Flat.•Created Spark and Hive jobs for data summarization and transformation.