Data Delivery Architect for AI-Ready Platforms

Amazon Web Services (AWS); Chicago (IL); On-site; USD 131,000 - 178,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

Amazon Web Services, Inc. is seeking a Delivery Consultant specializing in Data to join the ProServe team.

You will help clients become AI-ready by building data platforms, pipelines, and RAG architectures that empower foundation models and AI agents. You will design and implement production-grade data solutions (lake, lakehouse, mesh) and enable AI reasoning with governed data in regulated environments, often co-located on site with customer teams.

Qualifications

• 3+ years of cloud architecture and solution implementation experience.
• Knowledge of AWS services (EC2, ELB, RDS, Route53 & S3) is expected.
• Experience with data modeling, warehousing and building ETL pipelines.
• Bachelor's degree in business administration, finance, economics, computer science, data science, engineering, or related field.

Responsibilities

• Design and implement production-grade data pipelines, data lakes, lakehouses, and data mesh architectures within enterprise environments.
• Build data products that serve multiple downstream applications and use cases from AI/ML model training to agentic AI systems.
• Operate with autonomy in fast-moving delivery engagements and make judgment calls on data modelling and architecture.

Skills

Cloud architecture

Data modeling

ETL pipelines

AWS services

Data governance

Security & privacy

Education

Bachelor's degree

Tools

AWS services (EC2, S3, etc)

Job description

Amazon Web Services, Inc. is seeking a Delivery Consultant specializing in Data to join the ProServe team.

You will help clients become AI-ready by building data platforms, pipelines, and RAG architectures that empower foundation models and AI agents. You will design and implement production-grade data solutions (lake, lakehouse, mesh) and enable AI reasoning with governed data in regulated environments, often co-located on site with customer teams.