Remote Principal Data Architect for Enterprise AI

Burtch Works; United States; On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Competitive compensation package

Job summary

Burtch Works is seeking a Principal Data Architect – Enterprise AI to design and implement an enterprise-wide data architecture in a remote, US-wide setup. You will standardize data models, establish governance, and create architectural consistency across multiple SaaS products.

The ideal candidate has built enterprise data architecture from the ground up and can influence engineering, product, and executive leadership to drive AI-enabled growth.

Qualifications

• Education: Bachelor's degree in a technical field; Master's preferred.
• Experience: 10+ years in enterprise data architecture or engineering across multiple products.
• Proven ability to lead data standardization and governance in SaaS/fintech environments.

Responsibilities

• Lead Enterprise Data Architecture; design enterprise data models across products.
• Standardize data models to improve scalability and interoperability.
• Establish data governance, metadata strategies, and best practices.
• Enable enterprise AI by building foundational data architecture for ML and analytics.
• Influence cross-functional teams without direct authority.
• Drive business outcomes by reducing technical debt and speeding AI adoption.

Skills

Enterprise Data Modeling

Enterprise Data Architecture

Data Governance & Standardization

Azure Databricks

Delta Lake

Unity Catalog

SQL

PySpark

Master Data Management

Data Warehousing

Cloud Data Platforms

Enterprise Integration

Metadata Management

AI-Ready Data Architecture

Executive Stakeholder Management

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or related technical discipline

Master's degree preferred

Job description

Burtch Works is seeking a Principal Data Architect – Enterprise AI to design and implement an enterprise-wide data architecture in a remote, US-wide setup. You will standardize data models, establish governance, and create architectural consistency across multiple SaaS products.

The ideal candidate has built enterprise data architecture from the ground up and can influence engineering, product, and executive leadership to drive AI-enabled growth.