Enterprise Data Architect - Data Products & AI Enablement

Adept Consulting Services•Harrisburg, PA

12h

About The Position

Adept Consulting Services is seeking an experienced Enterprise Data Architect to help define and evolve enterprise information architecture and reusable data products supporting large-scale modernization, transformation, analytics, and artificial intelligence initiatives. This position will partner with business leaders, product teams, engineers, and enterprise technology stakeholders to determine which information assets should be shared across organizations and which should remain specific to individual business domains. The Enterprise Data Architect will define data domains, develop conceptual and logical data models, establish enterprise information standards, map legacy data sources to target domains, and help create the schemas, interfaces, metadata, and quality requirements needed to support modernization initiatives. This role serves as a critical bridge between business processes and technical implementation, ensuring that new solutions contribute to a sustainable enterprise data foundation rather than creating additional data silos.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Systems Programming, or a related discipline, or an equivalent combination of education and professional experience.
At least 10 years of experience in data architecture, information architecture, enterprise architecture, or a closely related area.
At least eight years of hands-on experience in data architecture, data engineering, advanced database design, or data modeling.
Demonstrated experience designing or implementing data warehouses, data marts, and enterprise data models.
Strong understanding of master data management concepts, practices, and tools.
At least five years of experience with modern data platforms and cloud-based data ecosystems, including technologies such as Snowflake, Databricks, MongoDB, AWS, Azure, or Google Cloud Platform.
Experience designing solutions that address data security, privacy, classification, and regulatory requirements for sensitive information.
Experience designing or implementing data-quality programs, platforms, or tools.
Demonstrated success supporting large-scale modernization or digital transformation initiatives across multiple business domains and stakeholder groups.
Strong understanding of metadata management, data lineage, data catalogs, governance, interoperability, and data observability.
Ability to translate complex business concepts into practical data models and technical architecture.
Strong written and verbal communication skills.
Ability to develop and manage independent work plans, resolve ambiguity, influence stakeholders, and lead teams without direct authority.

Nice To Haves

Experience within the public sector, healthcare, financial services, or another highly regulated environment.
Experience working with unstructured or semi-structured data.
Experience creating reusable enterprise data products.
Familiarity with semantic layers, knowledge graphs, natural-language data access, or AI-ready data architecture.
Previous experience as a Principal Architect, Enterprise Information Architect, Enterprise Data Architect, or Solution Architect supporting a large enterprise or modernization program.

Responsibilities

Define conceptual and logical data models for shared business entities.
Establish canonical data models and enterprise information standards.
Define relationships between enterprise-wide and domain-specific data assets.
Incorporate data classification, privacy, security, and regulatory requirements into architectural designs.
Develop architecture principles and standards that promote consistency, interoperability, and reuse.
Partner with product, engineering, and workflow-modernization teams to incorporate reusable data products into solution designs.
Analyze legacy systems and identify information assets suitable for enterprise reuse.
Prevent the unnecessary duplication of data structures across applications and organizations.
Support data migration strategies and the development of target-state architectures.
Provide data architecture guidance for large-scale modernization and digital transformation initiatives.
Identify opportunities to create reusable enterprise data products.
Define data-product schemas, interfaces, metadata, quality expectations, and service boundaries.
Establish ownership, stewardship, and governance models for enterprise data products.
Promote API-first and product-based approaches to information sharing.
Establish data architecture principles, standards, guidelines, and best practices.
Support data catalogs, lineage, observability, security, and interoperability capabilities.
Define common business terms, data definitions, and data-quality expectations.
Help design and implement data-quality initiatives, platforms, and supporting tools.
Introduce standards for metadata management, data ownership, and accountability.
Translate business concepts and processes into scalable technical designs.
Collaborate with cloud, integration, data engineering, and platform teams.
Provide architectural guidance for enterprise data platforms and information-sharing solutions.
Ensure designs support structured and, when applicable, unstructured data.
Ensure enterprise data products are discoverable, governed, reliable, and suitable for future AI and analytics use cases.
Support the development of semantic layers, knowledge graphs, and natural-language access to enterprise information.
Help establish the trusted data foundation necessary for responsible enterprise AI adoption.