Aws Quick or Amazon Quick Specialist

Role & responsibilities

AWS Quick Specialist

personally implemented Amazon Quick in real-world enterprise environments

Key Responsibilities

• Design and implement

  Amazon Quick

  dashboards, analyses, datasets, semantic models and enterprise BI solutions.
• Lead

  BI modernization and migration

  initiatives from platforms such as Tableau, Power BI or other legacy BI technologies to Amazon Quick.
• Work with customers to translate business and analytical requirements into scalable AWS-native solutions.
• Develop reusable frameworks, accelerators and best practices for Amazon Quick implementations.
• Integrate Amazon Quick with AWS data services including

  Amazon Redshift, Athena, S3, RDS, Glue and other AWS analytics services

  .
• Apply

  Generative AI and Agentic AI

  capabilities to analytics and BI use cases.
• Work hands-on with

  Amazon Bedrock

  , foundation models, knowledge bases, agents and enterprise AI patterns.
• Develop or contribute to solutions leveraging

  Amazon Quick Desktop / Quick capabilities

  and emerging AWS AI/analytics services.
• Gain working knowledge of

  Amazon Bedrock AgentCore

  and agentic application architectures.
• Collaborate with Solution Architects, Data Engineers, AI Engineers and customer stakeholders to deliver production-grade solutions.
• Support customer workshops, technical demonstrations, PoCs and solution design activities.

Must-Have Skills

• 810 years of overall technology experience.

• Strong hands-on experience with Amazon Quick is mandatory.

• Proven experience implementing

  Amazon Quick for enterprise customers

  — candidates with only training, certification or theoretical knowledge will not be suitable.
• Strong understanding of BI, analytics, dashboards, data visualization and semantic modeling.
• Hands-on experience with AWS analytics services such as

  Redshift, Athena, S3, Glue and RDS

  .
• Strong understanding of cloud-based data and analytics architectures.
• Experience with at least one enterprise BI platform such as

  Tableau, Power BI, Qlik or similar

  .
• Strong customer-facing communication and solutioning skills.

AI / GenAI Skills — Strong Advantage

• Amazon Bedrock

  — hands-on knowledge of foundation models, Knowledge Bases, Agents and GenAI application patterns.
• Understanding of

  Agentic AI architectures and autonomous AI agents

  .
• Exposure to

  Amazon Bedrock AgentCore

  and related agent development/orchestration capabilities.
• Experience integrating GenAI into analytics, BI or enterprise applications.
• Knowledge of RAG, embeddings, vector databases and prompt engineering.

• AWS Certified AI / Machine Learning certification

  or equivalent demonstrated expertise.

Preferred candidate profile

Perks and benefits