Data Architect Sr. Manager

Accenture
Mountain View, CA, United States
18 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Artificial Intelligence Cloud Computing Data Architecture Metadata Virtualization Technology

Requirements

DataArchitect Data Modeling Tool, Artificial Intelligence (AI), Ecosystems, Investment Strategy, Metadata, Cataloguing, DataArchitect Data Modeling Tool, Virtualization, Cloud Computing, Architectural Design

About the company

The beginning of a new Data & AI decade that will reshape work and society has begun. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimize and reinvent their business with data & AI - backed by a $3B investment and commitment to our people to do industry-defining work.

With over 45,000 professionals dedicated to Data & AI, Accenture’s Data & AI organization brings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem.

You Are:

You are a data/senior data architect who designs enterprise data fabric solutions that provide unified, intelligent, automated access to distributed data across on-prem and multi-cloud environments. You bring together data virtualization, active metadata, knowledge graphs, cataloging, and automated integration into a connected data layer that powers analytics and AI - and you can define the reference architectures and integration patterns that make it real.

The Work:

  • Architect enterprise data fabric - design data fabric solutions that deliver unified, intelligent, automated access to distributed data across on-prem and multi-cloud environments.
  • Integrate the connected data layer - design the integration of data virtualization, active metadata, knowledge graphs, cataloging, and automated data integration into a connected data layer for analytics and AI.
  • Define reference architectures - establish reference architectures, integration patterns, and governance integration that scale across the enterprise.
  • Enable data products and self-service - support self-service consumption, data products, and real-time data delivery through the fabric.
  • Apply modern data paradigms - bring data mesh and data product concepts, cloud data platforms (Snowflake, Databricks, Azure Synapse, BigQuery), and streaming/API architectures to bear on client problems.
  • Advise and shape solutions - engage client architects and leaders as a trusted advisor and shape solutions for major data modernization pursuits.

Travel may be required for this role, varying from 0 to 100% depending on business need and client requirements.

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