• Created Pipeline’s to extract data from on premises source systems to azure cloud data lake storage; extensively worked on copy activities and implemented the copy behaviors such as flatten hierarchy, preserve hierarchy and Merge hierarchy. Implemented Error Handling concept through copy activity.
• Exposure on Azure Data Factory activities such as Lookups, Stored procedures, if condition, for each, Set Variable, Append Variable, Get Metadata, Filter and wait.
• Create dynamic pipeline to handle multiple source extracting to multiple targets; extensively used azure key vaults to configure the connections in linked services.

Ø Configured and implemented the Azure Data Factory Triggers and scheduled the Pipelines; monitored the scheduled Azure Data Factory pipelines and configured the alerts to get notification of failure pipelines.

Ø Implemented delta logic extractions for various sources with the help of control table; implemented the Data Frameworks to handle the deadlocks, recovery, logging the data of pipelines.

• Reviewing individual work on ingesting data into azure data lake and provide feedbacks based on reference architecture, naming conventions, guidelines and best practices
• Developing Spark (Python) notebooks to transform and partition the data and organize files in ADLS
• Working on Azure Databricks to run Spark-Python Notebooks through ADF pipelines.
• Using Databricks utilities called widgets to pass parameters on run time from ADF to Databricks.
• Involved End-End logging frameworks for Data factory pipelines.
• Implemented delta logic extractions for various sources with the help of control table; implemented the Data Frameworks to handle the deadlocks, recovery, logging the data of pipelines.
• Extracted data from different sources such as Flat files, Oracle to load into SQL database.
• Involved in preparation and execution of the unit, integration and end to end test cases.

Agility Unite is an integration-driven umbrella that covers the entire marketing task flow from data ingestion to reporting and everything in between. It’s cloud-based marketing platform.

Roles & Responsibilities:

• Created Pipeline’s to extract data from on premises source systems to azure cloud data lake storage; extensively worked on copy activities and implemented the copy behaviors such as flatten hierarchy, preserve hierarchy and Merge hierarchy. Implemented Error Handling concept through copy activity.
• Exposure on Azure Data Factory activities such as Lookups, Stored procedures, if condition, for each, Set Variable, Append Variable, Get Metadata, Filter and wait.
• Create dynamic pipeline to handle multiple source extracting to multiple targets; extensively used azure key vaults to configure the connections in linked services.

Ø Configured and implemented the Azure Data Factory Triggers and scheduled the Pipelines; monitored the scheduled Azure Data Factory pipelines and configured the alerts to get notification of failure pipelines.

Ø Implemented delta logic extractions for various sources with the help of control table; implemented the Data Frameworks to handle the deadlocks, recovery, logging the data of pipelines.

• Reviewing individual work on ingesting data into azure data lake and provide feedbacks based on reference architecture, naming conventions, guidelines and best practices
• Developing Spark (Python) notebooks to transform and partition the data and organize files in ADLS
• Working on Azure Databricks to run Spark-Python Notebooks through ADF pipelines.
• Using Databricks utilities called widgets to pass parameters on run time from ADF to Databricks.
• Involved End-End logging frameworks for Data factory pipelines
• Implemented delta logic extractions for various sources with the help of control table; implemented the Data Frameworks to handle the deadlocks, recovery, logging the data of pipelines.
• Extracted data from different sources such as Flat files, Oracle to load into SQL database.
• Involved in preparation and execution of the unit, integration and end to end test cases.

Responsibilities

• As per the requirement write scripts and configured as report in Apex dashboard to monitor proactive monitoring of production issues
• Drill through Java code block to understand the client response code
• Run the shell scripts, Grant Hue access, Study folder creation in Unix as per business request
• Monitor files availability in Unix Directory, Clean the data from study folder
• Perform tool deployments in Unix, Analyze disk usage, clean unnecessary data of users
• Monitoring OEM to understand database performance issues.
• Monitoring the Informatica workflow progress for any latency in the dependent job triggering
• Identifying the cause of Workflow failure by logging in execption.log, node.log, catalena.out files
• Identifying application bugs in application releases and raising defects or Jira to Dev team.
• Developing scripts, Testing the changes in Lower Environment to handle the production issues and following with Development, QA team to get it approved. Create Knowledge Base Document.
• Raised Change Requests to move new changes/ Amendments into the system
• Worked on ActiveBatch to schedule/Enable/Disable jobs as per the business requirement
• Worked on Application/Database deployments in Unix/Windows Environment
• Create/Update system manual and Knowledge Base articles as per the new changes
• Investigate and resolve production issues as per agreed SLA. If necessary, escalate to the different stake holders based on the analysis
• Co-ordinating with Web logic team for Application performance issues.
• Resolved the issues reported by the users related to the data, XML issues

Responsibilities

• Analyzed and resolved the live incidents as per agreed SLA. If necessary, escalate to the different dealer groups based on the analysis.
• Strictly maintaining and following the SLA.
• Performed RCA of the Bridge cases and prepared detailed report of the same.
• Identify the production incidents/issues and fix them by making the necessary changes.
• Day to day troubleshooting Production issues and maintains the applications on Oracle.
• Creating and scheduling the jobs via Control-M to transfer the files, to run the reports.
• Perform sanity testing to ensure application is stable and functionality is working as per expectation as post release support.
• Implemented the standard nomenclature of Oracle, along with the standards of client
• Resolved the issues reported by the users related to the data, business issues.
• Raised many GCM’s to promote the changes to the production.
• Also involved in Database production releases.
• Coordinates/ facilitates transition (planning, sign-off, team meetings, and escalations).
• Handling failures during the Batch Run, Find the errors from the Unix box

 and fixing it along with known error data base.