PROJECTS PROFILE
Project#1 : ESG: Environment, Social and Governance
Environment :Microsoft Azure Storage,Azure Data Factory, ADLSGEN2
, Azure SQL-DB
Duration : June 2022 – till date
Description : Data Hub is a single Azure based environment to host the Data and MI Solutions
to deliver the core foundational aspects that will allow other business led
Projects to be delivered successfully.
Roles Responsibilities:
· HP project to provide metric details in automated way for developing Sustainability Impact report.
· Worked as ETL developer to develop the code and pipelines in Azure Data Factory which facilitated the incoming and outgoing of the data to and from on-premises.
· Responsible for taking care of the incremental loading of the data.
· Working as a key developer in Azure SQL database for creation and maintenance of stored procedures.
· Involved in debugging and solving bugs.
· Started to work on Azure Synapse Analytics
Project#2 : QBE Insurance DataHub
Client : QBE Insurance Group Pvt lmt
Environment : Microsoft Azure Storage,Azure Data Factory, ADLSGEN2
Azure Data Bricks, Spark and Scala, Azure SQL-DB
Duration : May 2021 – May 2022
Roles Responsibilities:
• Gathering information and analyzing the sources.
• Creating New ADF pipelines to ingest the data into DataHub from various sources.
• Responsible for creating or configuring the triggers.
• Creating Notebook using Pyspark in Azure data bricks and write logics
per the business requirements.
• Loading the data according to the target data model to Synapse.
• Reconcile the data at each layers of the DataHub.
• ADF is used to Orchestrate the data across layers.
• Followed the agile methodology in delivering and used Azure boards for
project management and Bugs tracking.
• Performing Unit and Integration testing before code merge.
Project#3
Title : MAS (Monetary Authority of Singapore)
Environment : Microsoft Azure Storage,Azure Data Factory,
Azure Data Bricks, Spark and Scala, Azure SQL-DB
Duration : April-2021 to May 2021
· Developing HQL queries as per Business Requirement in data bricks Notebooks .
· Implementing the data transformation or processing logics using Azure Databricks service with spark and scala.
· Create mount points for Azure services whit the help of Databricks Notebooks.
· Used azure Databricks notebook to write the spark code for Master Note book .
· Loading the transformed datasets into Azure SQL-DB using Azure data factory Pipeline.
· Invoke the emil-pipeline to get the status of pipeline and writing the stored procedures on SQL-DB to handle upserts.
· Developing data pipelines using Azure data factory to run the pipeline daily basis .