Azure Data Architect for AI-Ready Data Platforms

Clorox Company; Durham (NC); Hybrid; USD 109,000 - 259,000; Full time

Benefits offered by this job

Health plans

401(k) with company match

Flexible time off

Fertility/adoption benefits

Hybrid work model

Job summary

The Clorox Company is seeking an experienced Data Architect to join the Data Architecture & Strategy team. You will define and advance the enterprise data architecture, govern data platforms, and enable analytics, AI, and data products across the organization.

You will work with business units, platform vendors, and engineering teams to design, implement, and operate scalable data ecosystems, applying best practices in governance, modeling, and semantic layers.

Qualifications

• 8+ years in Data Architecture, Data Engineering, Analytics Architecture, or related fields.
• Experience designing enterprise-scale cloud data platforms and solutions.
• Strong knowledge of data governance, metadata management, data quality, and security architectures.

Responsibilities

• Define and evolve enterprise data architecture standards and reference architectures.
• Design scalable, secure, and governed data architectures for analytics, AI, and operations.
• Lead architecture for cloud-based data platforms using Azure technologies.
• Collaborate with business and tech teams to deliver enterprise data solutions.
• Promote data products and semantic layers for trusted analytics.

Skills

Data architecture

Cloud data platforms

Azure

Databricks

Power BI

Python

SQL

Communication

Leadership

CI/CD

Education

Bachelor’s degree in Computer Science, Information Systems, Engineering

Tools

Microsoft Fabric

Azure Data Factory

Databricks

Delta Lake

Power BI

ADLS

Job description

The Clorox Company is seeking an experienced Data Architect to join the Data Architecture & Strategy team. You will define and advance the enterprise data architecture, govern data platforms, and enable analytics, AI, and data products across the organization.

You will work with business units, platform vendors, and engineering teams to design, implement, and operate scalable data ecosystems, applying best practices in governance, modeling, and semantic layers.