Overview
Remote
On Site
Full Time
Skills
google cloud platform
Machine Learning (ML)
Root cause analysis
Data Analysis
Artificial intelligence
Business acumen
Business process
Data engineering
Data Science
Data integration
Functional requirements
Data
C
Analytics
Database
Cloud computing
Scalability
Testing
IMPACT
Estimating
Design
Leadership
Collaboration
Roadmaps
Software deployment
Exceed
Communication
Job Details
100% Remote Contract 1099 or C2C 6 -9 month plus
The primary role of the Data Architect is to support and expand the Data & Analytics platforms that process, store, organize the data critical for the data and analytics team. This role will have expertise in data movement and database technologies support data analytics and Machine Learning (ML) / Artificial Intelligence (AI) capabilities in the cloud. This person is able to identify performance bottle necks in complex enterprise applications and identify tuning opportunities
Requirements
Responsibilities
Possess deep functional and technical understanding of the Machine Learning technologies (Google's Cloud Platform) and leverage it across Client's large, complex and diverse landscape.
Analyze performance and scalability characteristics to identify bottlenecks in large-scale distributed systems
Perform root cause analysis of performance issues identified by internal testing and from customers and suggest corrective actions
Business acumen (strong understanding of how business operates, and how to harness data and analytics to meet business needs)
expert at designing as well as developing all layers of an application and platform
Leads the development of technology transitions or architecture evolutions by creating foundational examples of working solutions and coaches' teams on how to build on those examples
Engage early in project efforts to analyze current solutions, provide solution options and recommendations, understand business process impact, provide accurate estimates.
Design and Architect applications across multiple domains including Data Engineering, Data Science, Data Viz and App development.
Demonstrates deep understanding of business processes and technology building blocks
Lead collaboration with project teams, application, data, integration, infrastructure, and security enterprise architects to develop and deploy comprehensive solution architectures
Ensure projects are delivered in-line with design, roadmap and to the defined standards and best practices.
Is skilled as a Data Architect who can design end-to-end data driven solutions
Influences adoption working IT, Business and Architecture groups
Creates design considering data sources & dependencies, development landscape, deployment landscape.
Generate ideas and suggestions for process and technical improvements for platforms and processes supported by the team
Architect the Google Cloud Platform data platform to meet the non-functional requirements of the consumptions layer and solutions built on top of the data platform.
Identify potential performance and availability challenges proactively, implement recommendations, and ensure that the systems' capacity and availability exceed requirements while ensuring the platform achieves business results.
Partner with solution architects, data engineers, platform engineers and other team roles to assess the platform's needs, help design new capabilities, establish architectural roadmaps, design and run tests/proof-of-concepts, help troubleshoot problems, identify risks, and make recommendations.
Comfortable with communication across all levels of department and create artifacts to clearly deliver the message.
The primary role of the Data Architect is to support and expand the Data & Analytics platforms that process, store, organize the data critical for the data and analytics team. This role will have expertise in data movement and database technologies support data analytics and Machine Learning (ML) / Artificial Intelligence (AI) capabilities in the cloud. This person is able to identify performance bottle necks in complex enterprise applications and identify tuning opportunities
Requirements
Responsibilities
Possess deep functional and technical understanding of the Machine Learning technologies (Google's Cloud Platform) and leverage it across Client's large, complex and diverse landscape.
Analyze performance and scalability characteristics to identify bottlenecks in large-scale distributed systems
Perform root cause analysis of performance issues identified by internal testing and from customers and suggest corrective actions
Business acumen (strong understanding of how business operates, and how to harness data and analytics to meet business needs)
expert at designing as well as developing all layers of an application and platform
Leads the development of technology transitions or architecture evolutions by creating foundational examples of working solutions and coaches' teams on how to build on those examples
Engage early in project efforts to analyze current solutions, provide solution options and recommendations, understand business process impact, provide accurate estimates.
Design and Architect applications across multiple domains including Data Engineering, Data Science, Data Viz and App development.
Demonstrates deep understanding of business processes and technology building blocks
Lead collaboration with project teams, application, data, integration, infrastructure, and security enterprise architects to develop and deploy comprehensive solution architectures
Ensure projects are delivered in-line with design, roadmap and to the defined standards and best practices.
Is skilled as a Data Architect who can design end-to-end data driven solutions
Influences adoption working IT, Business and Architecture groups
Creates design considering data sources & dependencies, development landscape, deployment landscape.
Generate ideas and suggestions for process and technical improvements for platforms and processes supported by the team
Architect the Google Cloud Platform data platform to meet the non-functional requirements of the consumptions layer and solutions built on top of the data platform.
Identify potential performance and availability challenges proactively, implement recommendations, and ensure that the systems' capacity and availability exceed requirements while ensuring the platform achieves business results.
Partner with solution architects, data engineers, platform engineers and other team roles to assess the platform's needs, help design new capabilities, establish architectural roadmaps, design and run tests/proof-of-concepts, help troubleshoot problems, identify risks, and make recommendations.
Comfortable with communication across all levels of department and create artifacts to clearly deliver the message.