Enterprise Data Architect

Enterprise Data Architect

The Enterprise Data Architect is responsible for defining and evolving the Commonwealth’s enterprise information architecture and reusable data products to support transformation and AI priorities.

This role partners with business leaders, product and engineering teams, and the enterprise technology organization to identify which information assets should be shared across agencies and which should remain domain-specific. The position will define data domains, create data models, ensure data quality, map source to domain, and assist in creating contracts to support modernization initiatives and future AI capabilities.

The role serves as the bridge between business processes and technical implementation, ensuring that new solutions contribute to a sustainable enterprise data foundation rather than creating additional silos. The ideal candidate possesses a comprehensive understanding of data architecture principles, practical data modeling experience, and deep expertise in data-centric architecture.

Key Responsibilities

1. Enterprise Information Architecture

• Define conceptual and logical data models for common business entities.
• Establish canonical models and enterprise information standards.
• Define relationships between enterprise and domain-specific data assets.
• Design enterprise information architecture that incorporates data classification, privacy, security, and regulatory requirements by design.

2. Modernization Programs

• Partner with workflow modernization teams (product and engineering) to embed reusable data products into solution designs.
• Analyze legacy systems and identify information assets suitable for enterprise reuse.
• Prevent duplication of data structures across applications and agencies.
• Support data migration strategies and target-state architecture.

3. Data Product Architecture

• Identify and support the design of reusable data products.
• Define schemas, interfaces, metadata, and quality requirements.
• Establish product boundaries, stewardship, and ownership models.

4. Data Governance and Metadata

• Establish data architecture principles, data standards, best practices, and guidelines including data catalog, data lineage, observability, security, and interoperability.
• Define business definitions and data quality expectations.

5. Platform and Technology Collaboration

• Work with engineering and platform teams to translate business concepts into technical designs.
• Partner with cloud, integration, and data teams to implement enterprise data products.
• Promote API-first and product-based approaches to information sharing.

6. AI Enablement

• Ensure enterprise data products are discoverable, governed, and suitable for future AI use cases.
• Support semantic layers, knowledge graphs, and natural language access to enterprise information.

Success Measures

During the first year, this role will:

• Establish enterprise information architecture principles.
• Define reusable enterprise data products for priority domains.
• Support specific modernization initiatives as a model implementation.
• Introduce metadata and ownership standards.
• Enable future modernization efforts to reuse common data assets rather than recreating them.
• Lay the foundation for enterprise analytics and AI capabilities across the Commonwealth.

Desired Background and Experience

• Bachelor of Computer Science, Information Systems, Systems Programming, or equivalent combination of relevant education and experience.
• Ability to work across domains and stakeholders with strong communication skills.
• Proven ability to develop work plans for self, resolve ambiguity, and lead teams without authority.
• Industry experience in Public Sector, Healthcare, or Financial Services is preferable.
• Candidates may have previously served as Principal Architect, Enterprise Information Architect, or Solution Architect for large enterprises or modernization initiatives.

Candidate Skills and Qualifications

Required Experience:

• 10 Years: Experience in data architecture, information architecture, or enterprise architecture.
• 8 Years: Hands-on experience in data architecture, data engineering, or advanced database design, modeling experience in designing or implementing data warehouse/data marts, MDM concepts, and tools.
• 5 Years: Experience with data platforms such as Snowflake, Databricks, MongoDB, and big data on cloud-based ecosystems (AWS, Azure, GCP).
• Required: Experience working with data security, privacy, and regulatory requirements for handling sensitive data.
• Required: Experience in designing and implementing data quality initiatives, including platforms and tooling.
• Required: Experience supporting large-scale modernization or digital transformation initiatives across multiple domains and stakeholders.