Cloud Platform Architect for Data & AI (Snowflake/Databricks)

USEReady; Alpharetta (GA); On-site; USD 140,000 - 190,000; Full time

Job summary

USEReady in Alpharetta, GA is seeking an experienced Cloud Solutions Architect to design, implement, and govern modern cloud-based data and AI platforms.

You'll lead architectural standards, build CI/CD pipelines, and drive enterprise adoption of Snowflake/Databricks, GenAI, and ML technologies while collaborating with data scientists and software engineers. This 12-month engagement requires hands-on leadership and a strong DevOps mindset to accelerate innovation across the enterprise.

Qualifications

• 8+ years of experience designing and implementing enterprise cloud data platforms.
• Hands-on with Snowflake, Databricks or similar platforms.
• Proficient in Python and SQL.
• Experience building CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins).
• Azure cloud experience preferred.
• Understanding data warehousing, Delta Lake, lakehouse architecture.
• Familiarity with REST APIs, microservices, containers and Kubernetes.

Responsibilities

• Architect and implement scalable, secure cloud data platforms using Snowflake/Databricks.
• Lead POCs and evaluations for AI/ML capabilities.
• Define architecture standards, governance, security controls.
• Design end-to-end CI/CD pipelines for infra, data, ML, apps.
• Automate platform administration with Python, Bash, PowerShell.
• Collaborate with data scientists and engineers to deliver AI-powered solutions.
• Optimize performance, scalability, reliability, and costs.
• Conduct architecture reviews and establish engineering best practices.

Skills

Cloud data platforms

Python

SQL

CI/CD pipelines

Azure

REST APIs

Kubernetes

Tools

GitHub Actions

Azure DevOps

Jenkins

Job description

USEReady in Alpharetta, GA is seeking an experienced Cloud Solutions Architect to design, implement, and govern modern cloud-based data and AI platforms.

You'll lead architectural standards, build CI/CD pipelines, and drive enterprise adoption of Snowflake/Databricks, GenAI, and ML technologies while collaborating with data scientists and software engineers. This 12-month engagement requires hands-on leadership and a strong DevOps mindset to accelerate innovation across the enterprise.