Enterprise Technical / Data Architect
Role details
Job location
Tech stack
Job description
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Leads the Enterprise Data Architecture across the eco-system with focus on:
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Cloud Platforms in Google Cloud, AWS, and Salesforce
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On-premises and PaaS platforms such as Oracle, Corporate Systems, and Financial Systems
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Big Data Tools in Google Cloud
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ETL & Data Integration
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Data Governance & Quality
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Data Security
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Data Compliance & Residency
Responsible for cataloging and defining the Data architectural artifacts including Data Flows, Logical & Physical Data Models, Data integrations, and more.
Leads the architectural efforts of large, complex projects (e.g., a family of products or IT services) involving multiple vendors, multiple technologies, leading-edge technologies, and broad implications for architecture and develops roadmap incorporating industry best practices.
Supports the development of complex proposals related to integrating multiple architecture domains (i.e., process, application, data, infrastructure).
Manages the architectural lifecycle, ensuring that engineering and maintenance phases conform to the architecture.
Makes strategic decisions about system design, implementation, and maintenance.
Analyzes systems and processes from end to end.
Analyzes quality attributes of solutions and evaluates the technical and economic feasibility of proposed solutions.
Interacts with clients or senior management in geographically and/or socially diverse teams on strategic operations, serving as an expert in several specialties or components.
Participates as a member of a team to assess and recommend a migration strategy to new technologies.
Displays collaboration & leadership by leveraging communication skills to liaise with senior management, business leaders, and IT teams to ensure alignment on data strategy.
Enable cross-functional collaboration by working closely with software developers, data engineers, security teams, and business analysts to implement data solutions.
Stays current on the latest technologies and trends., * Enterprise Caching Architectures
- Messaging Based Architecture e.g. Kafka
- Micro Service Architecture
- Public Facing APIs and API Gateways
- Enterprise Integration Patterns
- Data Transformation and ETL
Hot Skills:
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Cloud Focused:
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Google Cloud & Big Query
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Salesforce and Data Cloud
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AWS and cloud-native architectures
Data Focused:
- Hospitality Data
- Big Data
- Relational Data
- BI Tools & Reporting (Tableau, Power BI, or Looker)
Requirements
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Data Focused:
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Data Warehouse ecosystems
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Data Design Principles and Best Practices
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Reporting and Analytics Design Platforms
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Data Platforms knowledge for Data Residency decisions
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BI tools
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Analytic Tools
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Decision Science Experience, including Machine Learning or Artificial Intelligence
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Forecast and Demand Planning Applications
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Master Data Management Applications
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Relational & NoSQL Databases