Enterprise Data Architect

About the role

The Enterprise Data Architect will define and evolve enterprise information architecture and reusable data products that support modernization, transformation, and future AI capabilities. This role will partner with business, product, engineering, and technology teams to establish data domains, develop data models, promote data quality and governance, and ensure enterprise data assets can be securely and effectively reused across initiatives.

Responsibilities

• Define conceptual and logical data models for common business entities and establish canonical models and enterprise information standards.
• Define relationships between enterprise and domain-specific data assets while incorporating data classification, privacy, security, and regulatory requirements.
• Partner with product and engineering teams to incorporate reusable data products into modernization and solution designs.
• Analyze legacy systems and identify information assets suitable for enterprise reuse.
• Identify opportunities to prevent duplication of data structures across applications and domains.
• Support data migration strategies and target-state architecture.
• Identify and support the design of reusable data products, including schemas, interfaces, metadata, and quality requirements.
• Establish data product boundaries, stewardship, and ownership models.
• Establish data architecture principles, standards, best practices, and guidelines covering data catalogs, lineage, observability, security, and interoperability.
• Define business definitions and data quality expectations.
• Translate business concepts into technical designs in collaboration with engineering and platform teams.
• Partner with cloud, integration, and data teams to implement enterprise data products.
• Promote API-first and product-based approaches to information sharing.
• Ensure enterprise data products are discoverable, governed, and suitable for future AI use cases.
• Support the development of semantic layers, knowledge graphs, and natural language access to enterprise information.

Requirements

• 10+ years of experience in data architecture, information architecture, or enterprise architecture.
• 8+ years of hands-on experience in data architecture, data engineering, or advanced database design, including experience designing or implementing data warehouses.
• 5+ years of experience with data platforms such as Snowflake, Databricks, and MongoDB, as well as big data on cloud-based ecosystems such as AWS, Azure, or GCP.
• Experience working with data security, privacy, and regulatory requirements for handling sensitive data.
• Experience designing and implementing data quality initiatives, including platforms and tooling.
• Experience supporting large-scale modernization or digital transformation initiatives across multiple domains and stakeholders.