Job Description :
Job Role: Data Fabric Consultant
Job location: Cambridge, MA
Job Duration: 6+ months
Roles and Responsibilities:
Data fabric is a single environment consisting of a unified architecture, and services or technologies running on that architecture, that helps organizations manage their data irrespective of where the data is located. The data fabric is able to absorb, integrate, and maintain the freshness of vast quantities of data in any number of formats. By using semantic standards, the data integration is even more powerful as are the queries and algorithms that can be applied to the fabric.
Consultant will
Work collaboratively with stakeholders and develop use cases for Data Fabric
Perform POC with tools - Denodo, At Scale, Dremio and/or any other tools – create point of view what is the right tool set for Biogen
Suggest the Roadmap for "Data Fabric" at Biogen
o Short Term Roadmap
o Long Term Roadmap
A true data fabric solution should have the following capabilities:
Autonomous data engineering: Just-in-time query optimization for speed and usage consumption that can anticipate the needs of the data consumer in a single framework, reducing the complexity of data management and adapting to the needs of the data consumer.
Unified data semantics: A workplace for all data for consumers to define business meaning and get a single-source-of-truth point regardless of structure, database technology, and deployment platform for a cohesive analytics experience.
Centralized data security & governance: A centralized security policy to decentralize access using the tenets of Zero Trust that are applied consistently across the infrastructure for all data whether in cloud, multi-cloud, hybrid, or on-premises deployments.
Data management visibility: The ability to measure data responsiveness, availability, reliability, and risk in a centralized workspace.
Agnostic to platform and application: An ability to quickly integrate with data platform or BI/ML application for freedom of choice for data managers and consumers alike.
Future-proofs infrastructure: Reduce the disruption of new technologies and data types while modernizing legacy systems to maximize investments. New infrastructure deployments are integrated without impact to existing infrastructure and deployments.
No need for data movement: Intelligent data virtualization creates a single representation of data from multiple, disparate sources without having to copy or move the data.