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Please pay attention to the qualifications here as this is not a Developer role. We are looking to hire Architect Level candidate with Minimum 15 + Years of experience. . The Position –Data (Cloud Platform) Architect The Data (Cloud Platform) Architect is responsible for architecting Data On-Cloud solutions. The ideal candidate would also be responsible for conceptualizing and architecting cloud solutions to meet today’s high demand in areas such as AIML, IoT, advanced analytics, open source, enterprise collaboration, microservices, serverless, etc.
The Data (Cloud Platform) Architect is responsible for delivering the next generation of Data Lake/Warehouse: Hybrid Cloud based virtualized data lake/ warehouse.
Responsibilities include evangelizing data on cloud solutions with customers, leading Business and IT stakeholders through designing a robust, secure and optimized data architectures including a focus towards metadata services, to maximize the use of disparate data in lakes. This role will work with internal data engineers in delivering big data solutions on cloud. Using Amazon AWS Google Cloud Platform public cloud technologies, the Data (Cloud Platform) Architect professionals implements state of the art, scalable, high performance Data On Cloud solutions that meet the need of today’s corporate and emerging digital applications.
The role of a big data solutions architect is a very technical one, but he or she should also have some other skills that are important in designing the right architecture for the right need. The big data solutions architect is responsible for the overall design and development of a vision that underlies a projected big data solution.
The Architect will also assess the information architecture maturity of the data with industry-accepted data architecture principles and standards. Identify gaps and drive towards standardization and adoption across the organization for modelling, security, quality, metadata, among others.
This role will also define data and application integration framework with the focus towards standardization and definition of standards and guidelines. Interaction with the Data & Engineering and IT Delivery teams to drive standardization across data architecture principles