aditya

• Extracting data from multiple sources, structured and unstructured, including SalesForce, Flat files, Oracle, Excel files, Big Data, and SQL Server.
• Data Modeling for Data Warehouse/Data Mart development, Data Analysis for different applications.
• Preparing ETL data pipelines using AWS data engineering tools like Glue, Redshift, EMR, S3.
• Utilizing Synapse technology for data processing and analytics.
• Involvement in overall SDLC, including requirement gathering, development, testing, debugging, deployment, documentation, production support, and extensive experience in project management.
• Complete utilization of data modeling concepts like star schema, snowflake schema, etc.
• Optimizing queries using different methods, involving manual as well as using tools.
• Migrating data from On-premises SQL to Cloud and Cloud to Cloud using Azure Data Factory with different types of Insurance products.
• Building big data pipelines using delta load or incremental load based on frequently used data from source and target.
• Loading live streaming using Azure Event Hub.
• Moving properties related data to from on-premises SQL Server and Oracle and Flat Files as a source.
• Created Event Handlers for the Packages Using Event Handler Tab for Error Handling.
• Working on Service tickets for existing ETLs in SSIS, SSAS, and reports.
• Troubleshoot tidal Jobs and software issues.Create procedure manuals.
• Use best practice standard for Tidal automation.Setup runtime users , workgroups , connections .
• Found error in Tidal Jobs and debug the failed jobs.
• Developed Power BI data models for financial reports.
• Working on all kinds of reports such as yearly, quarterly, monthly, and daily.
• Implementing CI/CD pipelines, enabling rapid and reliable software delivery.
• Worked closely with development, operations, and QA teams to bridge gaps and foster a culture of continuous improvement. Highlight any experience with collaboration tools like Slack, Jira, or Confluence that facilitate effective communication and teamwork in a DevOps environment
Worked on all kinds of transformations available in Power BI query editor.

Extracting data from multiple sources, structured and unstructured, including SalesForce, Flat files, Oracle, Excel files, Big Data, and SQL Server.
Data Modeling for Data Warehouse/Data Mart development.
Data Analysis for different applications.
Preparing ETL data pipelines using AWS data engineering tools like Glue, Redshift, EMR, S3.
Utilizing Synapse technology for data processing and analytics.
Involvement in overall SDLC, including requirement gathering, development, testing, debugging, deployment, documentation, production support, and extensive experience in project management.
Complete utilization of data modeling concepts like star schema, snowflake schema, etc.
Optimizing queries using different methods, involving manual as well as using tools.
Migrating data from On-premises SQL to Cloud and Cloud to Cloud using Azure Data Factory with different types of Insurance products.
Building big data pipelines using delta load or incremental load based on frequently used data from source and target.
Loading live streaming using Azure Event Hub.
Moving properties related data to from on-premises SQL Server and Oracle and Flat Files as a source.
Created Event Handlers for the Packages Using Event Handler Tab for Error Handling.
Working on Service tickets for existing ETLs in SSIS, SSAS, and reports.
Troubleshoot tidal Jobs and software issues.
Create procedure manuals.
Use best practice standard for Tidal automation.
Setup runtime users, workgroups, connections.
Found error in Tidal Jobs and debug the failed jobs.
Developed Power BI data models for financial reports.
Working on all kinds of reports such as yearly, quarterly, monthly, and daily.
Implementing CI/CD pipelines, enabling rapid and reliable software delivery.
Worked closely with development, operations, and QA teams to bridge gaps and foster a culture of continuous improvement.
Worked on all kinds of transformations available in Power BI query editor.

Migrating data from all sources, On-premises SQL to Cloud and Cloud to Cloud using Azure Data Factory with different types of Insurance products.
Created Snowflake Data warehouse to validate and generate analytics on the transformed data.
Experience with the spark improving the performance and optimization of the existing algorithms in Hadoop using spark context, spark sql, dataframe API, spark streaming, Mlib, Pair RDD’s and worked explicitly on Pyspark and Spark sql.
Hands on experience with Amazon s3, Amzon Glue, auto scaling, EMR and other services of the AWS family.
Building the pipelines using delta load or incremental load based on frequently used data from source and target.
Loading live streaming using Azure Event Hub.
Moving desktop details and other Insurance products data to On-premises SQL Server as a source.
Using Synapse technology for enhanced data processing and analytics.
Using Git for version control.
Involved in configuring the Hadoop Cluster for Dev and QA Environment.
Installed and configured Enterprise and Personal gateway in PowerBi Services.
Created Row level Security in Cubes, which can be used in PowerBi Reports.
Backfilled 500M+ records to Hive tables using Spark SQL Concepts.
Working on Service tickets for existing ETLs for Big Data in SSIS, SSAS, and reports.

Migrating data from On-premise to Cloud and Cloud to Cloud using Azure data factory with different types of oil and natural gas products.
Building the pipelines using delta load or incremental load based on frequently using data from source and target.
Involved in creating Hive table and then applied HiveQL on those table for data Validations.
Loading live streaming using Azure Event Hub.
Shipping desktop details and Other Petroleum products data is importing to On-premise SQL Server as a source.
Use Oracle, SQL, Salesforce, Flat files and other Source Data moved to DWH and then to Cloud.
From On-premise SQL Server as a source we are migrating to Azure Data Lake Storage(ADLS) as Landing then to Azure Analysis(Datawarehouse).
Used Control-M workload automation solution that enables us to automate the scheduling and processing of business workflows across various platforms and applications from a single point of control.
Once development environment process is finished, we are integrating azure code repository into Azure Devops.
Applied Query Tuning and Performance techniques to work smoothly with huge amounts of data of more than 20 million records.
Using Azure code repository with Git account we used to deploy the pipelines code into Testing and Production Environments.
From Production environment, we fetch the data from ADLS and used to create dashboards and reports in Power BI desktop & deploy into Power BI cloud service.

Creating Packages on SSIS by using different data Transformations like Derived Column, Lookup, Conditional Split, Merge Join, Script Component and Execute SQL Task to load data into Database.
Experience in requirement analysis, coding and testing various modules in a software development life cycle, designing database structure.
Extracting data from multiple sources like Excel files, flat files and SQL server for transforming, cleansing and validating the data and land into Azure Data Lake then to load into final Destination i.e. Azure Data Warehouse.
Designed packages in Azure DataFactory Using Control Flow Tasks like For Each Loop Container, Execute SQL Task and Data Flow Task.
Scheduling Jobs to execute SSIS packages.
Scheduling reports using Reporting services to e-mail with an attachment in the desired format of report to the top management.
Created Event Handlers for the Pipelines in Azure Data Factory using different methods.
Created Configurations to change the package properties dynamically.
Developing parameterized reports including multi-parameters.
Included various reporting features such as group by, drilldowns, drill through, sub-reports, navigation reports etc.
Applying Derived Column, Multicast and Conditional Split, Look UP, transformations while loading Data into DWH.

Build BI environment in Azure by Creating VMs in IAAS deployment mode, Configuring MS BI components and establishing connectivity among components in different VMs.
Provide solutions for reporting requests in the account.
Designed Microsoft Cloud BI platform in Azure, and Created Design principles for the Project.
Build Azure BI Platform in IAAS Mode by using Installing SQL server 2016 and using SSIS, SSAS and power BI.
Used Python to code for extracting files.
Build Azure PAAS model to Load Loggers Data from 3rd party API using Azure Data Factory and loaded into Azure Data Lake store and then into Azure SQL DWH.
Build Semantic model using Azure Analysis services.
Inherited the same security to SSAS tabular cubes and SSRS connecting SQL server as well as Cubes.
Implemented Power BI reports in Reporting server.
Implemented Power BI embedded Services to Embed Power BI reports in Application to give access to external users and Implemented RLS on those users.
Defined Process for Logical environmental setup In Power BI to deliver standard reports in Organization.
Explore new features like Power BI Report server and implemented in our project.
Applying Derived Column, Multicast and Conditional Split, Look UP, transformations while loading Data into DWH.

Extracting data from multiple sources like Flat files, Oracle, Excel files, and SQL server and transforming, cleansing, validating data and loading into final Destination.
Designed packages Using Control Flow Tasks like For Loop Container, ForEach Loop Container, Sequential Container, Execute SQL Task and Data Flow Task.
Extracted data from sources and transformed the data using different transformations like data conversion, derived columns, look up, Conditional Split, Aggregate, Union all, merge join and multi cast transformations.
Created Event Handlers for the Packages Using Event Handler Tab for Error Handling.
Created Configurations to change the package properties dynamically.
Maintained log information in SQL table to tracking Errors and recording package execution status.
Build and Deployed packages to SQL server and Scheduling Packages for Intra Day and End of Day execution.
As per requirements developed the reports in the form of Matrix, Table and Chart using SQL Server 2008r2/2012 Reporting Services.
Designed Different Types of reports like Drill Down, Drill Through, SubReports and Parameterized Reports.
Development of reports using different SSRS Functionalities like sort prompts and cascading parameters, Multi Value Parameters.
Good knowledge in using report manager and giving security according to roles hierarchy.
Scheduled Reports Weekly and Monthly basis as per the Client Requirements.