Hybrid Data Platform Architect — Cloud & AI

RiseMe; Glendale (AZ); Hybrid; USD 180,000 - 200,000; Full time

Benefits offered by this job

Hybrid work model

Competitive benefits

In-office collaboration Glendale, WI

Job summary

Johnson Controls is seeking an Enterprise Architect, Data Platform to define and govern the company-wide data architecture strategy. You will lead data lakehouse, streaming, and data product initiatives, guiding cloud adoption across AWS, Azure, and GCP while partnering with security, governance, and business teams for scalable, cost-effective data platforms.

The role drives AI/ML enablement, analytics capabilities, and data governance while aligning with enterprise standards and multi-cloud

Qualifications

• Bachelor's degree in CS, IS, engineering, or related field.
• 12+ years in enterprise technology and data architecture.
• 5+ years in Enterprise Architect or Senior Data Architect roles.
• Experience designing enterprise-scale cloud data platforms.
• Preferred TOGAF or equivalent certification.

Responsibilities

• Define and govern the enterprise data platform strategy and roadmap.
• Lead architecture across data lakehouse, streaming, data mesh, and data products.
• Define standards for batch/real-time processing, APIs, data virtualization.
• Collaborate with security, governance, and business leaders.
• Lead architecture review boards and ensure consistency.

Skills

Strategic thinking

Executive communication

Cross-functional collaboration

Decision making under ambiguity

Business acumen

Education

Bachelor's degree in CS/IS/Engineering

Master's degree preferred

Tools

Snowflake

Microsoft Fabric

Kafka

Dbt

Coalesce

Airflow

AWS

Azure

GCP

Job description

Johnson Controls is seeking an Enterprise Architect, Data Platform to define and govern the company-wide data architecture strategy. You will lead data lakehouse, streaming, and data product initiatives, guiding cloud adoption across AWS, Azure, and GCP while partnering with security, governance, and business teams for scalable, cost-effective data platforms.

The role drives AI/ML enablement, analytics capabilities, and data governance while aligning with enterprise standards and multi-cloud