Data Architect

About the role

This 12-month role prepares the Strategic Process Inventory (SPI) data estate for use by a GenAI platform. The Data Architect will define data onboarding approaches, identify required source structures, design performant access patterns, and ensure metadata is complete, accurate, and usable by downstream semantic and AI context layers. The position requires a hybrid work model with three days onsite at Plano, TX, Charlotte, NC, or Jersey City, NJ.

Responsibilities

• Identify and document required SPI Oracle database schemas, tables, views, and columns needed for GenAI.
• Define the onboarding scope for structured data, including source systems, subject areas, and key data products.
• Extract, validate, and organize technical metadata from Oracle using tools like Toad or SQL scripts.
• Establish and maintain metadata standards for table descriptions, column definitions, data types, and classifications.
• Collaborate with business and data SMEs to validate data accuracy and representation.
• Design optimized database views or materialized views to improve performance for GenAI query execution.
• Define aggregation, denormalization, and join strategies for common data access paths.
• Provide canonical source-to-target mapping between Oracle data structures and business concepts.
• Support the mapping of business terminology to physical Oracle tables and columns.
• Validate data quality, completeness, and referential consistency.
• Identify sensitive data elements requiring access controls and document data limitations.

Required Qualifications

• 8+ years of experience in enterprise data architecture, database architecture, or data platform architecture.
• Strong experience with Oracle relational databases and designing performant data access patterns for analytics, reporting, or AI-enabled query systems.
• Experience with metadata onboarding, data catalogs, and semantic modeling.
• Advanced SQL, particularly Oracle SQL, and a strong understanding of PL/SQL concepts.
• Proficiency with Oracle Database, Starburst, Toad for Oracle (or equivalent), data catalog platforms, and Git or other enterprise source control systems.
• Awareness of CI/CD for database scripts.

Preferred Qualifications

• Working knowledge of Python for metadata extraction, profiling, or automation.
• Familiarity with YAML / JSON metadata formats.
• Experience with enterprise process management systems such as POP or ARIS.
• Exposure to GenAI platforms and LLM-based enterprise solutions.
• Knowledge of regulatory and compliance-driven data environments.
• Experience with Airflow, dbt, Spark, or enterprise data pipeline tooling.