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Enterprise Architect IV/ Data Architect

Remote · USA Full-time New today

Enterprise Architect IV/ Data Architect Location: Madison, WI Top Skills & Years of Experience:

  • Industry experience with IT and information management – 10 years
  • Experience as a data architect or an architect leading complex technology solutions (includes data modeling) – 5 years
  • Experience working with both business and IT teams to co-design solutions that deliver measurable business value
  • Bachelor's Degree in Information Technology, or equivalent required

Nice to Have

Skills:

  • Experience defining and implementing data architecture for cloud solutions
  • Experience with public sector systems (insurance, pension), modernization projects, and data analytics ecosystems

Job Description: We have an immediate opening at the Department of Employee Trust Funds (ETF) for a Data Architect and Data Modeler. ETF is a state agency that is recognized as a leader in providing public employee benefit systems. This position provides leadership in data architecture and modeling with a strong focus on understanding business needs and ensuring data solutions support agency priorities across a multi-year, multi-phase modernization effort and other mission-critical initiatives. The modernization effort includes a “best of breed” implementation with different vendor solutions including enterprise content management (ECM), health insurance, pension, and other benefits systems. It is essential for an enterprise data architect/modeler to have both a business and technical focus because their role serves as a critical bridge between organizational goals and the systems that support them. A strong business focus ensures that data strategies and models align with the needs of stakeholders, support decision-making, and drive value across departments. At the same time, a deep technical understanding is necessary to design scalable, secure, and efficient data architectures that integrate with complex IT ecosystems. This dual focus enables the architect to translate business requirements into actionable technical solutions, ensure data quality and consistency, and future-proof the organization’s data assets in a rapidly evolving digital landscape.

Key Responsibilities

  • Collaborate closely with business leaders, technical teams, and vendors to understand business goals, processes, and data needs, ensuring architectural decisions are business-aligned.
  • Translate business objectives into data architecture requirements, partnering with technical staff to assess feasibility and execution.
  • Define and guide the agency’s enterprise data architecture, including the creation and ongoing maintenance of enterprise data flows, with a focus on how data moves across systems to support core business operations, analytics, and decision-making.
  • Provide direction and oversight for the design of data solutions, while leveraging technical staff to execute on specific implementation details and configurations.
  • Ensure understanding, application, and enforcement of enterprise data standards across systems and teams.
  • Recommend phased approaches to integrating new data sources and platforms in alignment with the agency’s modernization roadmap and long-term data strategy.
  • Lead data integration and migration planning to ensure accurate and efficient transitions between systems.
  • Collaborate with data stewards and data owners to provide regular updates on project progress and status.
  • Develop and maintain documentation on data architecture, data flows, and data models to ensure clarity and consistency.
  • Contribute to data governance frameworks that ensure data quality, consistency, and compliance with relevant policies and regulations.
  • Provide updates to leadership on architecture progress, risks, and contributions to agency-wide data and modernization efforts.
  • Contribute to and help evolve the agency’s enterprise data strategy, ensuring it supports both current needs and future growth.

Knowledge, Skills, and Experience

  • Experience in pension, retirement, or benefit distribution systems including health insurance and related data processes
  • Proficient in creating and maintaining Data Flow Diagrams (DFDs)
  • Experience enforcing enterprise data standards and managing enterprise vs. local data usage
  • Experience working with both transactional data models and applications, as well as data lake architectures and solutions
  • Proficiency with ERwin Data Modeler for developing, documenting, and maintaining logical and physical data models in support of enterprise architecture.
  • Strong business acumen with the ability to understand, synthesize, and translate business needs into high-level data architecture strategies.
  • Ability to collaborate with technical teams in the implementation of architecture, relying on their expertise for detailed solution design and execution.
  • Extensive experience leading data efforts in complex, multi-system environments, with a focus on integration and business impact.
  • Deep understanding of enterprise data management disciplines: data governance, master data, metadata, lineage, and quality.
  • Knowledge of data architecture principles, reference architectures, and best practices for both on-premises and cloud-based solutions.
  • Experience with data modeling tools and working with technical staff who focus on data integration technologies.
  • Strong communication and collaboration skills, with the ability to engage with business and technical stakeholders at all levels.
  • Strategic mindset with attention to data enablement, not just system architecture.

Qualifications

  • Bachelor’s degree in Information Technology, Computer Science, Business, or related field (or equivalent experience).
  • Minimum 10 years of experience in IT or data-related roles, with 5+ years in a lead data architecture capacity.
  • Experience working with both business and IT teams to co-design solutions that deliver measurable business value.
  • Preferred: Experience with public sector systems (insurance, pension), modernization projects, cloud data platforms, and data analytics ecosystems.

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