4 Job openings found

2 Opening(s)
2.0 Year(s) To 8.0 Year(s)
5.00 LPA TO 12.00 LPA
Responsibilities :   Collect and analyze technical requirements. Understand the design and architecture of our M365 apps development. Design and develop high-productivity M365 apps that leverage Add-In development APIs to the full extent. Integration of apps with Legal platform. Integration of apps with other Microsoft services like Azure AD, authentication flows, and Azure services. Performance optimization of ...
2 Opening(s)
4.0 Year(s) To 8.0 Year(s)
7.00 LPA TO 11.00 LPA
Responsibilities: Data engineering. Data pipeline development. Data quality/governance. Analyze and organize raw data. Data preparation for modeling. Aggregate and clean raw data from different sources. Explore ways to enhance data quality and reliability. Collaborate with data scientists and architects on projects   Skill Required: Solid understanding of SQL Server. Python. GitHub. Azure Data Factory. Azure Synapse. Data modeling. Microsoft Purview. Insurance industry experience. Exposure to Sales/Marketing domain. IMMEDIATE JOINING. Excellent English ...
5 Opening(s)
5.0 Year(s) To 8.0 Year(s)
15.00 LPA TO 20.00 LPA
Tasks/Duties: Communicate with stakeholders at all stages of the project cycle to understand requirements and explain limitations. Responsible for implementing, automating, deploying, monitoring, troubleshooting and administering our application's infrastructure & designing Databases. The candidate will take responsibility for the availability, performance, infrastructure security and scalability of our applications. Ability to translate business requirements into ...
5 Opening(s)
5.0 Year(s) To 8.0 Year(s)
15.00 LPA TO 20.00 LPA
Tasks/Duties: Communicate with stakeholders at all stages of the project cycle to understand requirements and explain limitations. Structure and design the data landscape of the organization. Look further on the following topics: Data availability: Connecting, moving, and generating datasets for consumption. Transformation: Feature creation, data cleansing, re-expression. Visualization: Exploratory data analysis, intuitive presentation of findings. Dashboarding: Guiding ...

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