Senior Data Architect: Enterprise Data & AI Platform

Insight Global; Minneapolis (MN); On-site; USD 140,000 - 190,000; Full time

Job summary

Insight Global is seeking a Senior Data Architect to lead the strategy, design, and optimization of the enterprise data ecosystem. You will focus on improving data quality, governance, and cost efficiency while shaping scalable, AI-ready architectures for large-scale datasets.

The role requires guiding cross-functional teams, defining standards, and aligning technology investments with business and product objectives. A proven record in enterprise data modeling and governance is essential.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 7+ years leading enterprise data architecture and governance initiatives.
• Experience designing/implementing data warehouses, data lakes, analytical platforms, data models, semantic layers, and governance programs.
• Proven expertise in conceptual, logical, and physical data modeling.
• Strong understanding of metadata management, data lineage, MDM, data quality, cataloging, stewardship, and lifecycle management.
• Experience defining enterprise-wide data standards, policies, governance operating models, and reusable architecture patterns.

Responsibilities

• Lead strategy, design, and optimization of the organization's enterprise data ecosystem.
• Improve data quality and governance; validate architecture decisions and reduce cloud/platform costs.
• Define scalable future-state architecture for AI and advanced analytics readiness.
• Partner with business leaders, product teams, Data Engineers, Java Engineers, and analytics stakeholders to establish enterprise data models and governance frameworks.

Skills

Enterprise Data Architecture

Data Governance

Data Modeling

Data Warehousing

Big Data Platforms

Education

Bachelor's degree in Computer Science/IT/Engineering

Job description

Insight Global is seeking a Senior Data Architect to lead the strategy, design, and optimization of the enterprise data ecosystem. You will focus on improving data quality, governance, and cost efficiency while shaping scalable, AI-ready architectures for large-scale datasets.

The role requires guiding cross-functional teams, defining standards, and aligning technology investments with business and product objectives. A proven record in enterprise data modeling and governance is essential.