Yasharth, Azure Cloud Engineer | Bench Resource on Contract | April 2024

Yasharth (RID : zcxyl3lftr90)

Azure Cloud Engineer

Location : New Delhi, India,

Experience : 1 Year

Rate: $25 / Hourly

Availability : 1 Week

Work From : Offsite

Category : Information Technology & Services

Shortlisted : 71

Total Views : 196

Key Skills

Azure Data Factory Azure Cloud

Discription

Professional Summary

Having 21 years of experience as an Azure Cloud Engineer with experience on Modern Data Platform.
My primary contribution to the team is to collaborate and provide robust cloud solutions to enhance commercial reporting, identify the scope of growth, minimize manual efforts to increase the efficiency of the process, and deal with real-time business reporting issues.
Led team of 25+ members as a Transition SPOC for new projects.

Education

Bachelor Of Technology: Ajay Kumar Garg Engineering College

AKTU – Ghaziabad, Uttar Pradesh

Skills

Azure Data Factory
Azure Data Lake
ETL
Data warehouse
SSMS
SQL
SSIS

Experience

ABC Company – Azure Cloud Engineer

Duration (Jan 2020 - Jan 2021 )

Responsibilities

Orchestrated a solution for Supply Chain planning Team and cruise customer support team to fulfil customers required order to be delivered at required location.
Real time Purchase Orders fulfilled with the help of integration of Azure services( Logic Apps, Data Factory, Azure Databricks, SQL DB, ADLS Gen 2.
Collaborated with a team of 7 Data engineers to created a CRM solution for client which enable insights about the business and help to build a scalable sales process.
Derived a systematic leaderboard solution for tracking Corporate Account Managers Win, loss, Net New Business and pipeline amounts
Enhanced commercial reporting project for client on Data lake application in Azure cloud which extract data from sources(SAP, SAM, MDS), involves data transformations (ADF, Databricks and Logic Apps) and provides updated data accessible to business users(Cubes, SSMS) to pull reports to Power BI.

Key Highlights :

Reduced order processing time by 60% which improved production efficiency in Suppy Chain Project.
Reduced number of major incidents by 23% through problem management.
Enhanced the model to enable backups of data and to create Data quality alerts.
Eliminated 40% of manual checks for monitoring, and decreased SLA breaches for client reporting by 15%.

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