Suyati Technologies Private Limited
2nd Floor, B-Wing,
Azure Data Engineer
Position : Azure Data Engineer
Location : Kochi/ Bangalore
Experience : 3-5 Years
Bachelor’s or Master’s degree in Engineering
3-4 years of solid development experience on .NET, SQL SERVER & Azure
Minimum of 2 years of experience in Azure Data Engineering
Hands on experience in Azure Data Factory, Azure Data Lake Storage & Analytics, Azure SQL
Hands on experience in .NET, ASP.NET MVC, C#, and Web API
Hands on experience in developing Azure Web Apps, and Azure App Services on Visual
Experience writing and maintaining ETLs, which operate on a variety of large structured and
Experience in handling structured and unstructured data.
Hands on experience in SQL Server, to write and optimize queries
Ability to technically troubleshoot, diagnose, isolate and correct data, long running queries
and database issues
Security in Azure public cloud – Traffic Manager, Azure Front door, Application gateway, Web
Application Firewall, Network Security, Azure AD
Software development full lifecycle methodologies, patterns, frameworks, libraries, and
Proficient understanding of distributed computing principles.
Proficient with .NET Core development using C#
Azure Synapse Analytics, Azure Data Bricks, Logic Apps, Azure Functions/durable functions
Azure API Management & Azure Key Vault
Azure DevOps & Terraform
Exposure to with big data tools such as Hadoop, Spark, Kafka, etc. is a plus
Build analytics tools that utilize the data pipeline to provide actionable insights into customer
acquisition, operational efficiency and other key business performance metrics.
Software prototyping and construction – Design, Build, and Modify existing business-tier
components, Web applications, and database objects using Microsoft platform technologies
(ASP.NET Web API) and Azure.
Work with stakeholders including the Executive, Product, Data and Design teams to assist
with data-related technical issues and support their data infrastructure needs.
Create and maintain the optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business
Build the infrastructure required for ELT from a wide variety of data sources.
Work with data and analytics experts to strive for greater functionality in our data systems.