Enterprise Cloud Data Architect - AI & Data Strategy Hybrid

Devopsroles; Missouri; Hybrid; USD 189,000 - 227,000; Full time

Benefits offered by this job

Equal Opportunity Employer

Competitive pay range

Job summary

Devopsroles is seeking an Enterprise Cloud Data Architect to define, design, and govern the next-generation enterprise data ecosystem. You will set the cloud data strategy on Google Cloud Platform, champion a Data as a Product mindset, and ensure data assets are secure, scalable, and AI-ready across the organization.

You will lead the development of data governance, reference architecture, and modern AI foundations while collaborating with Security, Compliance, and DevOps teams.

Qualifications

• Bachelor’s degree in CS, Engineering, MIS, or related field.
• 10+ years in enterprise data architecture.
• Proficient in GCP core services and data governance.
• Strong Python, Spark, and SQL skills.
• Experience with AI data foundations and vendor platforms.

Responsibilities

• Shape the enterprise Data Strategy and define the Enterprise Data Reference Architecture; lead technical design, own reusable patterns, and apply systems thinking.
• Develop data management best practices and frameworks for scalable architectures.
• Expert on data ingestion into Enterprise DataLake and Medallion Architecture.
• Define and maintain conceptual, logical, and physical data models; establish taxonomy, metadata standards, and semantic layer.

Skills

Enterprise data architecture

GCP data services

Data modeling

Python

Spark / PySpark

Education

Bachelor's degree in CS/Engineering/MIS

Master's preferred

Tools

BigQuery

Terraform

Airflow

DataPlex

Pub/Sub

Job description

Devopsroles is seeking an Enterprise Cloud Data Architect to define, design, and govern the next-generation enterprise data ecosystem. You will set the cloud data strategy on Google Cloud Platform, champion a Data as a Product mindset, and ensure data assets are secure, scalable, and AI-ready across the organization.

You will lead the development of data governance, reference architecture, and modern AI foundations while collaborating with Security, Compliance, and DevOps teams.