Data Integration Architect

**No 3rd Parties or Sponsorship!

Role Title: Data Integration Architect

Duration: 6 months with possible ext until EOY

Preferred Location: Prefer local to Milwaukee or within driving distance so can be onsite for meetings as needed

Role Description:
The Data Integration Architect is responsible for defining and governing enterprise data flow architecture. This role focuses on how data moves, transforms, is governed, and becomes trusted across systems to support operational excellence, reporting, analytics, automation, and emerging AI capabilities.

While integration technologies are part of the landscape, the primary emphasis of this role is establishing scalable, reusable, and observable data movement patterns aligned to business domains.

This architect ensures enterprise data is treated as a strategic asset structured, documented, secured, and designed for long-term sustainability rather than one-off project solutions.

This role requires strong communication and documentation skills to translate complex data architecture concepts into clear standards, reference designs, and actionable guidance for technical teams and business stakeholders.

Enterprise Data Flow Architecture

• Define and maintain enterprise standards for end-to-end data flows across operational, ERP, analytical, and external systems.
• Establish patterns for data ingestion, transformation, distribution, and synchronization (batch, streaming, CDC, event-driven where applicable).
• Design canonical data models and domain-aligned data structures to reduce redundancy and improve reuse.
• Define and govern data contracts between producing and consuming systems.
• Reduce point-to-point data dependencies in favor of scalable, maintainable architecture patterns.
• Contribute to the evolution of an enterprise data platform strategy.

Data-as-a-Product & Governance Enablement

• Promote a data-as-a-product mindset by defining reusable, discoverable, and governed data assets.
• Partner with business and technical stakeholders to define data ownership and stewardship expectations.
• Establish standards for data quality validation, lineage, and traceability.
• Support master data management alignment across systems and domains.
• Ensure enterprise data assets are documented, versioned, and lifecycle-managed.

Analytics & AI Enablement

• Architect data flows that support trusted reporting, advanced analytics, automation, and AI-driven initiatives.
  Ensure enterprise data is structured and accessible in ways that support AI consumption while maintaining security and governance controls.
  Identify gaps in data readiness that may inhibit analytics or AI initiatives.

Requirements:

• Bachelor''s Degree in Computer Science, Information Systems, Engineering, or related field (or equivalent experience).
• 7+ years of experience in data architecture, data integration, ETL/ELT, or enterprise data engineering.
• Experience designing data flows across hybrid cloud and on-premises environments.
• Strong understanding of data modeling concepts, including normalized models, dimensional models (star/snowflake schemas), and canonical data structures.
• Experience establishing data quality, governance, and lifecycle management standards.
• Working knowledge of APIs and data exchange patterns.
• Strong documentation skills including architecture diagrams, standards documentation, and data flow specifications.
• Demonstrated ability to communicate complex technical concepts to both technical and non-technical audiences.